# Epistemic Logic

*First published Fri Jun 7, 2019*

Epistemic logic is a subfield of epistemology concerned with logical
approaches to knowledge, belief and related notions. Though any logic
with an epistemic interpretation may be called an *epistemic
logic*, the most widespread type of epistemic logics in use at
present are modal logics. Knowledge and belief are represented via the
modal operators *K* and *B*, often with a subscript
indicating the agent that holds the attitude. Formulas
\(K_{a}\varphi\) and \(B_{a}\varphi\) are then read “agent
*a* knows that phi” and “agent *a* believes that
phi”, respectively. Epistemic logic allows the formal
exploration of the implications of epistemic principles. For example,
the formula \(K_{a}\varphi\rightarrow\varphi\) states that what is
known is true, while \(K_{a}\varphi\rightarrow K_{a}K_{a}\varphi\)
states that what is known is known to be known. The semantics of
epistemic logic are typically given in terms of possible worlds
*via* Kripke models such that the formula \(K_{a}\varphi\) is
read to assert that \(\varphi\) is true in all worlds agent *a*
considers epistemically possible relative to its current information.
The central problems that have concerned epistemic logicians include,
for example, determining which epistemic principles are most
appropriate for characterizing knowledge and belief, the logical
relations between different conceptions of knowledge and belief, and
the epistemic features of groups of agents. Beyond philosophy proper,
epistemic logic flourishes in theoretical computer science, economics,
and related fields.

- 1. Introduction
- 2. The Modal Approach to Knowledge
- 3. Knowledge in Groups
- 4. Logical Omniscience
- Bibliography
- Academic Tools
- Other Internet Resources
- Related Entries

## 1. Introduction

Aristotelian texts set the groundwork for discussions of the logic of
knowledge and belief, particularly *De Sophisiticis Elenchis*
as well as the *Prior* and *Posterior Analytics*. While
Aristotle addressed the four alethic modes of possibility, necessity,
impossibility, and contingency, Buridan, Pseudo Scotus, Ockham, and
Ralph Strode, helped to extend Aristotle’s insights to epistemic
themes and problems (Boh 1993; Knuuttila 1993). During this period,
the Pseudo-Scot and William of Ockham supplemented Aristotle’s
study of mental acts of cognition and volition (see Boh 1993: 130).
Ivan Boh’s studies of the history of fourteenth and fifteenth
century investigations into epistemic logic provide a excellent
coverage of the topic, especially his *Epistemic Logic in the Later
Middle Ages* (1993).

According to Boh, the English philosopher Ralph Strode formulated a
fully general system of propositional epistemic rules in his
influential 1387 book *Consequences* (Boh 1993: 135).
Strode’s presentation built on the earlier logical treatises of
Ockham and Burley. Problems of epistemic logic were also discussed
between the 1330s and 1360s by the so-called Oxford Calculators, most
prominently by William Heytesbury and Richard Kilvington. By the
fifteenth century, Paul of Venice and other Italian philosophers also
engaged in sophisticated reflection on the relationship between
knowledge, truth, and ontology.

Discussions of epistemic logic during the medieval period share a
similar set of foundational assumptions with contemporary discussions.
Most importantly, medieval philosophers explored the connection
between knowledge and veracity: If I know *p*, then *p* is
true. Furthermore, many medieval discussions begin with an assumption
similar to G.E. Moore’s observation that an epistemic agent
cannot coherently assert “*p* but I do not believe (know)
*p*”. Sentences of this form are generally referred to as
*Moore sentences*.

Modern treatments of the logic of knowledge and belief grew out of the
work of philosophers and logicians writing from 1948 through the
1950s. Rudolf Carnap, Jerzy Łoś, Arthur Prior, Nicholas
Rescher, G.H. von Wright and others recognized that our discourse
concerning knowledge and belief admits of an axiomatic-deductive
treatment. Among the many important papers that appeared in the 1950s,
von Wright’s seminal work (1951) is widely acknowledged as
having initiated the formal study of epistemic logic as we know it
today. Von Wright’s insights were extended by Jaakko Hintikka in
his book *Knowledge and Belief: An Introduction to the Logic of the
Two Notions* (1962). Hintikka provided a way of interpreting
epistemic concepts in terms of possible world semantics and as such it
has served as the foundational text for the study of epistemic logic
ever since.

In the 1980s and 1990s, epistemic logicians focused on the logical properties of systems containing groups of knowers and later still on the epistemic features of so-called “multi-modal” contexts. Since the 1990s work in dynamic epistemic logic has extended traditional epistemic logic by modeling the dynamic process of knowledge acquisition and belief revision. In the past two decades, epistemic logic has come to comprise a broad set of formal approaches to the interdisciplinary study of knowledge and belief.

Interest in epistemic logic extends well beyond philosophers. Recent decades have seen a great deal of interdisciplinary attention to epistemic logic with economists and computer scientists actively developing the field together with logicians and philosophers. In 1995 two important books signaled the fertile interplay between computer science and epistemic logic: Fagin, Halpern, Moses, and Vardi (1995) and Meyer and van der Hoek (1995). Work by computer scientists has become increasingly central to epistemic logic in the intervening years.

Among philosophers, there is increased attention to the interplay between these formal approaches and traditional epistemological problems (See for example, van Benthem 2006; Hendricks & Symons 2006; Stalnaker 2006; Holliday 2018).

Several introductory texts on epistemic logic exist, e.g., van Benthem (2011); Ditmarsch, Hoek, and Kooi (2007); Ditmarsch et al. (2015); Gochet and Gribomont (2006); and Meyer (2001) with Lenzen (1980) providing an overview of early developments.

## 2. The Modal Approach to Knowledge

Until relatively recently, epistemic logic focused almost exclusively
on propositional knowledge. In cases of propositional knowledge, an
agent or a group of agents bears the propositional attitude of knowing
towards some proposition. For example, when one says: “Zoe knows
that there is a hen in the yard”, one asserts that Zoe is the
agent who bears the propositional attitude *knowing* towards
the proposition expressed by the English sentence “there is a
hen in the yard”. Now imagine that Zoe does not know whether
there is a hen in the yard. For example, it might be the case that she
has no access to information about whether there is or is not a hen in
the yard. In this case her lack of information means that she will
consider two scenarios as being possible, one in which there is a hen
in the yard and one in which there is not.

Perhaps she has some practical decision that involves not only hens but also the presence of frightening dogs in the yard. She might wish to feed the hens but will only do so if there is no dog in the yard. If she were ignorant of whether there is a dog in the yard, the number of scenarios she must consider in her deliberations grows to four. Clearly, one needs to consider epistemic alternatives when one does not have complete information concerning the situations that are relevant to one’s decisions. As we shall see below, possible worlds semantics has provided a useful framework for understanding the manner in which agents can reason about epistemic alternatives.

While epistemic logicians had traditionally focused on *knowing
that,* one finds a range of other uses of knowledge in natural
language. As Wang (2015) points out, the expressions *knowing
how*, *knowing what*, *knowing why* are very common,
appearing almost just as frequently (sometimes more frequently) in
spoken and written language as *knowing that*. Recently
non-standard epistemic logics of such expressions have been developed,
though *knowing who* constructions are present in
Hintikka’s *Knowledge and Belief* (1962; see also
Boër & Lycan 1986; Rendsvig 2012). Thus, beyond propositional
knowledge, epistemic logic also suggests ways to systematize the logic
of questions and answers (Brendan knows why the dog barked). It also
provides insight into the relationships between multiple modes of
identification (Zoe knows that this man is the president). Here, the
agent can be said to know a fact relating multiple modes of
identification insofar as she correctly identifies the president, who
she might know from stories in the newspaper with the man she sees
standing in front of her, who she identifies as an object in her
visual field (Hintikka & Symons 2003). Epistemic logic may also
provide insight into questions of procedural “know-how”
(Brendan knows how to change a fuse). For example, knowing how to
\(\varphi\) can be understood to be equivalent to the claim that there
exists a way such that an agent knows that it is a way to ensure that
\(\varphi\) (see Wang 2015, 2018). Work concerning the justifications
of knowledge have also been undertaken by combinations of
*justification logic* with epistemic logic (see, e.g., Artemov
& Nogina 2005; Renne 2008). There is ongoing work on these and
other topics, and new developments are appearing steadily.

### 2.1 The Formal Language of Epistemic Logic

Recent work in epistemic logic relies on a modal conception of knowledge. In order to be clear about the role of modality in epistemic logic it is helpful to introduce the basic elements of the modern formalism. For the sake of simplicity we begin with the case of knowledge and belief for a single agent, postponing consideration of multiple agents to Section 3,

A prototypical epistemic logic language is given by first fixing a set
of *propositional variables* \(p_{1}\), \(p_{2}\),…. In
applications of epistemic logic, propositional variables are given
specific interpretations: For example, \(p_{1}\) could be taken to
represent the proposition “there is a hen in the yard” and
\(p_{2}\) the proposition “there is a dog in the yard”,
etc. The propositional variables represent propositions which are
represented in no finer detail in the formal language. As such, they
are therefore often referred to as *atomic propositions* or
simply *atoms*. Let *Atom* denote the set of atomic
propositions.

Apart from the atomic propositions, epistemic logic supplements the language of propositional logic with a modal operator, \(K_{a}\), for knowledge and \(B_{a}\), for belief.

\(K_{a}\varphi\) reads “Agent *a* knows that
\(\varphi\)”

and similarly

\(B_{a}\varphi\) reads “Agent *a* believes that
\(\varphi\)”.

In many recent publications on epistemic logic, the full set of
formulas in the language is given using a so-called *Backus-Naur
Form* (BNF). This is simply a notational technique derived from
computer science that provides a recursive definition of the formulas
deemed grammatically “correct”, i.e., the set
of *well-formed formulas*:

It should noted that the Greek letter \(\varphi\) stands for
the *syntactic category* of formula. So this definition says:
an atom *p* is a formula; \(\neg\varphi\) is a formula if
\(\varphi\) is a formula (read \(\neg\) as ‘it is not the case
that’); \((\varphi\wedge\varphi)\) is a formula whenever any two
formulas are connected by the \(\wedge\) symbol (read \(\wedge\) as
‘and’); and \(K_{a}\varphi\) and \(B_{a}\varphi\) are
formulas whenever \(\varphi\) is a formula (the readings were
indicated above). Note that in a non-BNF recursive specification of
the language, the Greek variable \(\varphi\) would be used
a *metavariable* ranging over formulas, and one would normally
state the clause for conjunctions as: \((\varphi \wedge \psi)\) is a
formula whenever \(\varphi\) and \(\psi\) are formulas. But the BNF
let's us get away with just using \(\varphi\) to get the same
effect.

We will call this basic language that includes both
a *K*nowledge and a *B*elief operator,
\(\mathcal{L}_{KB}\). As in propositional logic, additional
connectives are defined from \(\neg\) and \(\wedge\): Typical notation
is ‘\(\vee\)’ for ‘or’,
‘\(\rightarrow\)’ for ‘if…, then
…’ and ‘\(\leftrightarrow\)’ for
‘… if, and only if, …’. Also typically
\(\top\) (‘top’) and \(\bot\) (‘bottom’) is
used to denote the constantly true proposition and the constantly
false proposition, respectively.

As we shall see below, \(K_{a}\varphi\) is read as stating that
\(\varphi\) holds in *all* of the worlds accessible to
*a*. In this sense, *K* can be regarded as behaving
similarly to the ‘box’ operator, \(\square\), often used
to denote necessity. In evaluating \(K_{a}\varphi\) at a possible
world *w*, one is in effect evaluating a *universal
quantification* over all the worlds accessible from *w*. The
universal quantifier \(\forall\) in first-order logic has the
existential quantifier \(\exists\) as its *dual*: This means
that the quantifiers are mutually definable by taking either
\(\forall\) as primitive and defining \(\exists x\varphi\) as short
for \(\neg\forall x\neg\varphi\) or by taking \(\exists\) as primitive
and defining \(\forall x\varphi\) as \(\neg\exists x\neg\varphi\). In
the case of \(K_{a}\), it may be seen that the formula \(\neg
K_{a}\neg\varphi\) makes an *existential quantification*: It
says that there *exists* an accessible world that satisfies
\(\varphi\). In the literature, a dual operator for \(K_{a}\) is often
introduced. The typical notation for \(\neg K_{a}\neg\) includes
\(\langle K_{a}\rangle\) and \(\widehat{K}_{a}\). This notation mimics
the diamond-shape \(\lozenge\), which is the standard dual operator to
the box \(\square\), which in turn is standard notation for the
universally quantifying modal operator (see the entry on
modal logic).

More expressive languages in epistemic logic involve the addition of
operators for various notions of group knowledge (see
Section 3).
For example, as we discuss below, the *common knowledge*
operator and so-called *dynamic* operators are important
additions to the language of epistemic logic. Dynamic operators can
indicate for example the *truthful public announcement* of
\(\varphi\): \([\varphi!]\). A formula \([\varphi!]\psi\) is read
“if \(\varphi\) is truthfully announced to everybody, then after
the announcement, \(\psi\) is the case”. The question of what
kinds of expressive power is added with the addition of operators is a
research topic that is actively being investigated in
dynamic epistemic logic.
So, for example, adding \([\varphi!]\) by itself to
\(\mathcal{L}_{KB}\) does *not* add expressive power, but in a
language that also includes common knowledge, it does.

### 2.2 Higher-Order Attitudes

Notice that for example \(K_{a}K_{a}p\) is a formula in the language
we introduced above. It states that agent *a* knows that agent
*a* knows that *p* is the case. Formula with *nested*
epistemic operators of this kind express a *higher-order*
attitude: an attitude concerning the the attitude of some agent.

Higher-order attitudes is a recurring theme in epistemic logic. The aforementioned Moore sentences, e.g., \(B_{a}(p\wedge B_{a}\neg p)\) express a higher-order attitude. So do many of the epistemic principles discussed in the literature and below. Consider the following prominent epistemic principle involving higher-order knowledge: \(K_{a}\varphi\rightarrow K_{a}K_{a}\varphi\). Is it reasonable to require that knowledge satisfies this scheme, i.e., that if somebody knows \(\varphi\), then they know that they know \(\varphi\)? In part, we might hesitate before accepting this principle in virtue of the higher-order attitude involved. This is a matter of ongoing discussion in epistemic logic and epistemology.

### 2.3 The Partition Principle and Modal Semantics

The semantics of the formal language introduced above is generally
presented in terms of so-called possible worlds. In epistemic logic
possible worlds are interpreted as epistemic alternatives. Hintikka
was the first to explicitly articulate such an approach (1962). This
is another central feature of his approach to epistemology which
continues to inform developments today. It may be stated,
simplified,^{[1]}
as follows:

**Partition Principle:** Any propositional attitude
partitions the set of possible worlds into those that are in
accordance with the attitude and those that are not.

The partition principle may be used to provide a semantics for the knowledge operator. Informally,

\(K_{a}\varphi\) is true in world *w* if, and only if,
\(\varphi\) is true in every world \(w'\) compatible with what
*a* knows at *w*.

Here, agent *a* knows that \(\varphi\) just in case the agent has
information that rules out every possibility of error and rules out every
case where \(\neg\varphi\).

### 2.4 Kripke Models and The Indistinguishability Interpretation of Knowledge

Since the 1960s *Kripke models*, defined below, have
served as the basis of the most widely used semantics for all
varieties of modal logic. The use of Kripke models in the
representation of epistemic concepts involves taking a philosophical
stance with respect to those concepts. One widespread interpretation,
especially in theoretical economics and theoretical computer science,
understands knowledge in terms of informational indistinguishability
between possible worlds. What we will refer to here as the
*indistinguishability interpretation* goes back at least to
Lehmann (1984).

As the indistinguishability interpretation concerns knowledge, but not belief, we will be working with a language without belief operators. Therefore, let the language \(\mathcal{L}_{K}\) be given by the Backus-Naur form

\[\varphi:=p\mid \neg\varphi\mid (\varphi\wedge\varphi)\mid K_{a}\varphi\text{ for } p\in \textit{Atom}.\]As we shall see, the indistinguishability interpretation involves very stringent requirements in order for something to qualify as knowledge. We introduce it here for pedagogical purposes, putting the formal details of the interpretation in place so as to introduce and explain relatively less extreme positions thereafter.

Consider again the case of Zoe, the hen, and the dog. The example involves two propositions, which we will identify with the formal atoms:

*p* read as “there is a hen in the yard”.

and

*q* read as “there is a dog in the yard”.

It is worth emphasizing that for the purposes of our formalization of
this scenario, these two are the *only* propositions of
interest. We are restricting our attention to
\(\textit{Atom}=\{p,q\}\). In early presentations of epistemic logic
and in much of standard epistemic logic at present, *all* the
atoms of interest are included from the outset. Obviously, this is an
idealized scenario. It is important to notice what this approach
leaves out. Considerations that are not captured in this way include
the appearance of novel atoms; the idea that other atomic propositions
might be introduced at some future state via some process of learning
for example, or the question of an agent’s awareness of
propositions; the scenario in which an agent might be temporarily
*unaware* of some atom due to some psychological or other
factor (see
Section 4
for references to so-called *awareness logic*). For now, the
main point is that standard epistemic logic begins with the assumption
that the set *Atom* exhausts the space of propositions for the
agent.

With two atoms, there are four different ways a world could consistently be. We can depict each by a box:

The four boxes may be formally represented by a set
\(W=\{w_{1},w_{2},w_{3},w_{4}\}\), typically called a set of
** possible worlds**. Each world is further
labeled with the atoms true at that world. They are labeled by a
function

*V*, the

**. The valuation specifies which atoms are true at each world in the following way: Given an atom**

*valuation**p*, \(V(p)\) is the subset of worlds at which

*p*is true.

^{[2]}That \(w_{1}\) is labeled with

*p*and

*q*thus means that \(w_{1}\in V(p)\) and \(w_{1}\in V(q)\). In the illustration, \(V(p)=\{w_{1},w_{2}\}\) and \(V(q)=\{w_{1},w_{3}\}\).

For presentational purposes, assume that there really is a hen in the
yard, but no dog. Then \(w_{2}\) would represent the
** actual world** of the model. In illustrations,
the actual world is commonly highlighted:

Now, assume that the hen is always clucking, but that the dog never
barks, and that although Zoe has acute hearing, she cannot see the
yard. Then there are certain possible worlds that Zoe cannot
*distinguish*: possible ways things may be which she cannot
tell apart. For example, being in the world with only a hen \((p,\neg
q)\), Zoe cannot tell if she is in the world with both hen and dog
\((p,q)\): her situation is such that Zoe is aware of two ways things
could be but her information does not allow her to eliminate
either.

To illustrate that one possible world cannot be distinguished from another, an arrow is typically drawn from the former to the latter:

Here, arrows represent a *binary relation* on possible worlds.
In modal logic in general, it is referred to as the
** accessibility relation**. Under the
indistinguishability interpretation of epistemic logic, it is
sometimes called the

**. Formally, denote the relation \(R_{a}\), with the subscript showing the relation belongs to agent**

*indistinguishability relation**a*. The relation is a subset of the set of

*ordered pairs*of possible worlds, \(\{(w,w')\colon w,w'\in W\}\). One world

*w*“points” to another \(w'\) if \((w,w')\in R_{a}\). In this case, \(w'\) is said to be

*accessible*(

*indistinguishable*) from

*w*. In the literature, this is often written \(wR_{a}w'\) or \(R_{a}ww'\). The notation ‘\(w'\in R_{a}(w)\)’ is also common: the set \(R_{a}(w)\) is then the worlds accessible from

*w*, i.e.,

A final note: the set \(\{(w,w')\colon w,w'\in W\}\) is often written
\(W\times W\), the *Cartesian product* of *W* with
itself.

For \(R_{a}\) to faithfully represent a relation of
indistinguishability, what worlds should it relate? If Zoe was plunged
in \(w_{1}\) for example, could she tell that she is not in \(w_{2}\)?
No: the relation of indistinguishability is *symmetric*if one
cannot tell *a* from *b*, neither can one tell *b* from
*a*. That a relation is symmetric is typically drawn by omitting
arrow-heads altogether or by putting them in both directions:

Which of the remaining worlds are indistinguishable? Given that the
hen is always clucking, Zoe has information that allows her to
distinguish \(w_{1}\) and \(w_{2}\) from \(w_{3}\) and \(w_{4}\) and
*vice versa*, cf. symmetry. Hence, no arrows between these. The
worlds \(w_{3}\) and \(w_{4}\) are indistinguishable. This brings us
to the following representation:

Since no information will ever allow Zoe to distinguish something from
itself, any possible world is thus related to itself and the
indistinguishability relation is *reflexive*:

The standard interpretation of the Zoe example in terms of a possible worlds model is now complete. Before turning to a general presentation of the indistinguishability interpretation, let us look at what Zoe knows.

Recall the informal modal semantics of the knowledge operator from above:

\(K_{a}\varphi\) is true in world *w* if, and only if,
\(\varphi\) is true in every world \(w'\) compatible with the
information *a* has at *w*.

To approach a formal definition, take ‘\(w\vDash\varphi\)’
to mean that \(\varphi\) is true in world *w*. Thus we can,
define truth of \(K_{a}\varphi\) in *w* by

\(w\vDash K_{a}\varphi\) iff \(w'\vDash\varphi\) for all \(w'\) such that \(wR_{a}w'\).

This definition states that *a* knows \(\varphi\) in world
*w* if, and only if, \(\varphi\) is the case in all the worlds
\(w'\) which *a* cannot distinguish from
*w*.

So, where does that leave Zoe? First off, the definition allows us to evaluate her knowledge in each of the worlds, but seeing as \(w_{2}\) is the actual world, it is the world of interest. Here are some examples of what we can say about Zoe’s knowledge in \(w_{2}\):

- \(w_{2}\vDash K_{a}p\). Zoe knows that the hen is in the yard as
all the worlds indistinguishable from \(w_{2}\) that would be
\(w_{1}\) and \(w_{2}\) make
*p*true. - \(w_{2}\vDash\neg K_{a}q\). Zoe does not know that the dog is in
the yard, as one of the indistinguishable worlds in fact \(w_{2}\)
itself makes
*q*false. - \(w_{2}\vDash K_{a}K_{a}p\). Zoe knows that she knows
*p*because \(a)\) \(w_{2}\vDash K_{a}p\) (cf. 1.) and \(b)\) \(w_{1}\vDash K_{a}p\). - \(w_{2}\vDash K_{a}\neg K_{a}q\). Zoe knows that she does not know
*q*because \(a)\) \(w_{2}\vDash\neg K_{a}q\) (cf. 2.) and \(b)\) \(w_{1}\vDash\neg K_{a}q\).

We could say a lot more about Zoe’s knowledge: every formula of the epistemic language without belief operators may be evaluated in the model. It thus represents all Zoe’s higher-order information about her own knowledge of which points 3. and 4. are the first examples.

One last ingredient is required before we can state the
indistinguishability interpretation in its full generality. In the
example above, it was shown that the indistinguishability relation was
both *symmetric* and *reflexive*. Formally, these
properties may be defined as follows:

**Definition:** A binary relation \(R\subseteq W\times
W\) is

iff for all \(w\in W,wRw\),*reflexive*iff for all \(w,w'\in W,\) if \(wRw'\), then \(w'Rw\).*symmetric*

The missing ingredient is then the relational property of
*transitivity*. ’Shorter than’ is an example of a
transitive property: Let *x* be shorter than *y*, and let
*y* be shorter than *z*. Then *x* must be shorter than
*z*. So, given \(w_{1},w_{2}\) and \(w_{3}\), if the relation
*R* holds between \(w_{1}\) and \(w_{2}\) and between \(w_{2}\)
and \(w_{3}\), then the arrow between \(w_{1}\) and \(w_{3}\) is the
consequence of requiring the relation to be transitive:

Formally, transitivity is defined as follows:

**Definition:** A binary relation \(R\subseteq W\times
W\) is ** transitive** iff for all \(w,w',w''\in
W,\) if \(wRw'\) and \(w'Rw''\), then \(wRw''\)

A relation that is both reflexive, symmetric and transitive is called
an ** equivalence relation**.

With all the components in place, let us now define the Kripke model:

**Definition:** A ** Kripke model**
for \(\mathcal{L}_{K}\) is a tuple \(M=(W,R,V)\) where

*W*is a non-empty set of possible worlds,*R*is a binary relation on*W*, and- \(V\colon \textit{Atom} \longrightarrow\mathcal{P}(W)\) is a valuation.

In the definition, ‘\(\mathcal{P}(W)\)’ denotes the
*powerset* of *W*: It consists of all the subsets of
*W*. Hence \(V(p)\), the valuation of atom *p* in the model
*M*, is some subset of the possible worlds: Those where *p*
is true. In this general definition, *R* can be any relation on
*W*.

To specify which world is actual, one last parameter is added to the
model. When the actual world is specified a Kripke model is commonly
called *pointed*:

**Definition:** A ** pointed Kripke
model** for \(\mathcal{L}_{K}\) is a pair \((M,w)\)
where

- \(M=(W,R,V)\) is a Kripke model, and
- \(w\in W\).

Finally, we may formally define the semantics that was somewhat
loosely expressed above. This is done by defining a relation between
pointed Kripke models and the formulas of the formal language. The
relation is denoted ‘\(\vDash\)’ and is often called the
** satisfaction relation**.

The definition then goes as follows:

**Definition:** Let \(M=(W,R_{a},V)\) be a Kripke model
for \(\mathcal{L}_{K}\) and let \((M,w)\) be a pointed Kripke model.
Then for all \(p\in \textit{Atom}\) and all
\(\varphi,\psi\in\mathcal{L}_{K}\)

The formula \(\varphi\) is ** satisfied** in the
pointed model \((M,w)\) iff \((M,w)\vDash\varphi\).

In full generality, the indistinguishability interpretation holds that
for \(K_{a}\) to capture knowledge, the relation \(R_{a}\) must be an
equivalence relation. A pointed Kripke model for which this is
satisfied is often referred to as an ** epistemic
state**. In epistemic states, the relation is denoted by a
tilde with subscript: \(\sim_{a}\).

Given pointed Kripke models and the indistinguishability
interpretation, we have a semantic specification of one concept of
knowledge. With this approach, we can build models of situations
involving knowledge as we did with the toy example of Zoe and the
hens. We can use these models to determine what the agent does or does
not know. We also have the formal foundations in place to begin asking
questions concerning how the agent’s knowledge or uncertainty
develops when it receives *new information*, a topic studied in
dynamic epistemic logic.

We may also ask more general questions concerning the concept of knowledge modeled using pointed Kripke models with indistinguishability relations: Instead of looking at a particular model at the time and asking which formulas the model makes true, we can ask which general principles all such models agree on.

### 2.5 Epistemological Principles in Epistemic Logic

Settling on the correct formal representation of knowledge involves reflecting carefully on the epistemological principles to which one is committed. An uncontroversial example of such a principle which most philosophers will accept is veridicality:

*If a proposition is known, then it is true*.

In a formal context this principle can be understood to say that if \(\varphi\) is known then it should always be satisfied in one’s models. If it turns out that some of one’s chosen models falsify the veridicality principle, then most philosophers would simply deem those models unacceptable.

Returning to pointed Kripke models, we can now ask which principles
these models commit one to. In order to begin answering this question,
we need to understand the most general features of our formalism. The
strategy in modal logic in general (see Blackburn, de Rijke, &
Venema 2001) is to abstract away from any given model’s
*contingent* features. Contingent features would include, for
example, the specific number of worlds under consideration, the
specific valuation of the atoms, and the choice of an actual world. In
this case, the only features that are not contingent are those
required by the general definition of a pointed Kripke model.

To abstract suitably, take a pointed Kripke model \((M,w)=(W,R,V,w)\).
To determine whether the relation of this model is an equivalence
relation we only need to consider the worlds and the relation. The
pair of these elements constitute the fundamental level of the model
and is called the *frame* of the model:

**Definition:** Let \((M,w)=(W,R,V,w)\) be a pointed
Kripke model. Then the pair \((W,R)\) is called the
** frame** of \((M,w)\). Any model \((M',w')\)
which shares the frame \((W,R)\) is said to be

**\((W,R)\).**

*built on*Consider again the epistemic state for Zoe from above:

Several other models may be built on the same frame. The following are two examples:

With the notion of a frame, we may define the notion of validity of interest. It is the second term defined in the following:

**Definition:** A formula \(\varphi\) is said to be
** valid in the frame** \(F=(W,R)\) iff every
pointed Kripke model build on

*F*satisfies \(\varphi\), i.e., iff for every \((M,w)=(F,V,w)=(W,R,V,w)\), \((M,w)\vDash\varphi\). A formula \(\varphi\) is

**\(\mathsf{F}\) (written \(\mathsf{F}\vDash\varphi\)) iff \(\varphi\) is valid in every frame**

*valid on the class of frames**F*in \(\mathsf{F}\).

The set of formulas valid on a class of frames \(\mathsf{F}\) is
called the ** logic** of \(\mathsf{F}\). Denote
this logic that is, the set
\(\{\varphi\in\mathcal{L}_{K}\colon\mathsf{F}\vDash\varphi\}\) by
\(\Lambda_{\mathsf{F}}\). This is a

*semantic*approach to defining logics, each just a set of formulas. One may also define logics

*proof-theoretically*by defining a logic as the set of formulas provable in some system. With logics as just sets of formulas,

*soundness*and

*completeness*results may then be expressed using set inclusion. To exemplify, let \(\mathsf{A}\) be a set of axioms and write \(\mathsf{A}\vdash\varphi\) when \(\varphi\) is provable from \(\mathsf{A}\) using some given set of deduction rules. Let the resulting logic the set of theorems be denoted \(\Lambda_{\mathsf{A}}\). It is the set of formulas from \(\mathcal{L}_{K}\) provable from \(\mathsf{A}\), i.e., the set \(\{\varphi\in\mathcal{L}_{K}\colon\mathsf{A}\vdash\varphi\}\). The logic \(\Lambda_{\mathsf{A}}\) is sound with respect to \(\mathsf{F}\) iff \(\Lambda_{\mathsf{A}}\subseteq\Lambda_{\mathsf{F}}\) and complete with respect to \(\mathsf{F}\) iff \(\Lambda_{\mathsf{F}}\subseteq\Lambda_{\mathsf{A}}\).

^{[3]}

Returning to the indistinguishability interpretation of knowledge, we may then seek to find the epistemological principles which the interpretation is committed to. There is a trivial answer of little direct interest: Let \(\mathsf{EQ}\) be the class of frames with equivalence relations. Then the logic of the indistinguishability interpretation is the set of formulas of \(\mathcal{L}_{K}\) which are valid over \(\mathsf{EQ}\), i.e., the set \(\Lambda_{\mathsf{EQ}}:=\{\varphi\in\mathcal{L}_{K}\colon\mathsf{EQ}\vDash\varphi\}\). Not very informative.

Taking an *axiomatic* approach to specifying the logic,
however, yields a presentation in terms of easy to grasp principles.
To start with the simplest, then the principle T states that knowledge
is *factual*: If the agent knows \(\varphi\), then \(\varphi\)
must be true. The more cumbersome K states that if the agent knows an
implication, then if the agent knows the antecedent, it also knows the
consequent. I.e., if we include the derivation rule *modus
ponens* (from \(\varphi\rightarrow\psi\) and \(\varphi\), conclude
\(\psi\)) as rule of our logic of knowledge, K states that knowledge
is *closed under implication*. The principle B states that if
\(\varphi\) is true, then the agent knows that it considers
\(\varphi\) possible. Finally, 4 states that if the agent knows
\(\varphi\), then it knows that it knows \(\varphi\). T, B and 4 in
the table below (the names are historical and not all meaningful).

In lieu of epistemological intuitions, we could discuss a concept of
knowledge by discussing these and other principles. Should we accept T
as a principle that knowledge follows? What about the others? Before
we proceed, let us first make clear how the four above principles
relate to the indistinguishability interpretation. To do so, we need
the notion of a *normal modal logic*. In the below definition,
as in the above principles, we are technically using *formula
schemas*. For example, in \(K_{a}\varphi\rightarrow\varphi\), the
\(\varphi\) is a variable ranging over formulas in
\(\mathcal{L}_{K}\). Thus, strictly speaking,
\(K_{a}\varphi\rightarrow\varphi\) is not a formula, but a
*scheme* for obtaining a formula. A *modal instance* of
\(K_{a}\varphi\rightarrow\varphi\) is then the formula obtained by
letting \(\varphi\) be some concrete formula from \(\mathcal{L}_{K}\).
For example, \(K_{a}p\rightarrow p\) and \(K_{a}(p\wedge
K_{a}q)\rightarrow(p\wedge K_{a}q)\) are both modal instances of
T.

**Definition:** Let \(\Lambda\subseteq\mathcal{L}_{K}\)
be a set of modal formulas. Then \(\Lambda\) is a ** normal
modal logic** iff \(\Lambda\) satisfies all of the
following:

- \(\Lambda\) contains all modal instances of the classical propositional tautologies.
- \(\Lambda\) contains all modal instances of K.
- \(\Lambda\) is closed under
*modus ponens*: If \(\varphi\in\Lambda\) and \(\varphi\rightarrow\psi\in\Lambda\), then \(\psi\in\Lambda\). - \(\Lambda\) is closed under
*generalization*(a.k.a.*necessitation*): If \(\varphi\in\Lambda\), then \(K_{a}\varphi\in\Lambda\).

There is a unique *smallest* normal modal logic (given the set
*Atom*)that which contains exactly what is required by the
definition and *nothing more*. It is often called the
** minimal normal modal logic** and is
denoted by the boldface

**K**(not to be confused with the non-boldface K denoting the schema).

The logic **K** is just a set of formulas from
\(\mathcal{L}_{K}\). I.e.,
**K** \(\subseteq\mathcal{L}_{K}\). Points 1.4.
gives a perspective on this set: They provide an
*axiomatization*. Often, as below, the schema K is referred to
as an axiom, though really the instantiations of K are axioms.

To **K**, we can add additional principles as axioms
(axiom schemes) to obtain stronger logics (logics that have additional
theorems: Logics \(\Lambda\) for which
**K **\(\subseteq\Lambda\)). Of immediate interest
is the logic called **S5**:

**Definition:** The logic **S5** is the
smallest normal modal logic containing all modal instances of T, B,
and 4.

Here, then, is the relationship between the above four principles and the indistinguishability interpretation:

**Theorem 1:** The logic **S5** is the logic
of the class of pointed Kripke models build on frames with equivalence
relations. I.e., \(\textbf{S5} =\Lambda_{\mathsf{EQ}}\).

What does this theorem tell us with respect to the principles of
knowledge, then? In one direction it tells us that if one accepts the
indistinguishability interpretation, then one has implicitly accepted the
principles K, T, B and 4 as reasonable for knowledge. In the other
direction, it tells us that if one finds that **S5** is
the appropriate logic of knowledge *and* one finds that pointed
Kripke models are the right way to semantically represent knowledge,
then one must use an equivalence relation. Whether one should
interpret this relation in terms of indistinguishability, though, is a
matter on which logic is silent.

In discussing principles for knowledge, it may be that some of the
four above seem acceptable, while others do not: One may disagree with
the acceptability of B and 4, say, while accepting K and T. In
understanding the relationship between **S5** and
equivalence relations, a more fine-grained perspective is beneficial:
Theorem 1 may be chopped into smaller pieces reflecting the
contribution of the individual principles K, T, 4 and B to the
equivalence requirementi.e., that the relation should be at the same
time reflexive, symmetric and transitive.

**Theorem 2:** Let \(F=(W,R)\) be a frame. Then:

- All modal instances of K are valid in
*F*. - All modal instances of T are valid in
*F*iff*R*is reflexive. - All modal instances of B are valid in
*F*iff*R*is symmetric. - All modal instances of 4 are valid in
*F*iff*R*is transitive.

There are a number of insights to gain from Theorem 2. First, if one
wants to use *any* type of Kripke model to capture knowledge,
then one must accept K. Skipping some details, one must in fact accept
the full logic **K** as this is the logic of the class of
*all* Kripke models (see, e.g., Blackburn, de Rijke, &
Venema 2001).

Second, the theorem shows that there is an intimate relationship between the individual epistemic principles and the properties on the relation. This, in turn, means that one, in general, may approach the “logic” in epistemic logic from two sides from intuitions about the accessibility relation or from intuitions about epistemic principles.

Several normal modal logical systems weaker than **S5**
have been suggested in the literature. Here, we specify the logics by
the set of their modal axioms. For example, the logic
**K** is given by \(\{\text{K}\}\), while
**S5** is given by
\(\{\text{K},\text{T},\text{B},\text{4}\}\). To establish
nomenclature, the following table contains a selection of principles
from the literature with the frame properties they characterize, cf.
Aucher (2014) and Blackburn, de Rijke, & Venema (2001), on the
line below them. The frame conditions are not all straightforward.

In Table 1, the subscript on \(R_{a}\) is omitted to ease readability,
and so is the domain of quantification *W* over which the worlds
variables \(x,y,z\) range.

K | \(K_{a}(\varphi\rightarrow\psi)\rightarrow(K_{a}\varphi\rightarrow
K_{a}\psi)\)
None: Not applicable |

D | \(K_{a}\varphi\rightarrow\widehat{K}_{a}\varphi\)
Serial: \(\forall x\exists y,xRy\). |

T | \(K_{a}\varphi\rightarrow\varphi\)
Reflexive: \(\forall x,xRx\). |

4 | \(K_{a}\varphi\rightarrow K_{a}K_{a}\varphi\)
Transitive: \(\forall x,y,z,\text{if }xRy\text{ and }yRz\text{, then }xRz\). |

B | \(\varphi\rightarrow K_{a}\widehat{K}_{a}\varphi\)
Symmetric: \(\forall x,y,\text{if }xRy\text{, then }yRx\). |

5 | \(\neg K_{a}\varphi\rightarrow K_{a}\neg K_{a}\varphi\)
Euclidean: \(\forall x,y,z,\text{if }xR_{a}y\text{ and }xR_{a}z\text{, then }yRz\). |

.2 | \(\widehat{K}_{a}K_{a}\varphi\rightarrow
K_{a}\widehat{K}_{a}\varphi\)
Confluent: \(\forall x,y,\text{if }xRy\text{ and }xRy',\text{ then }\exists z,yRz\text{ and }y'Rz\). |

.3 |
\((\widehat{K}_{a}\varphi\wedge\widehat{K}_{a}\psi)\rightarrow(\widehat{K}_{a}(\varphi\wedge\widehat{K}_{a}\psi)\vee\widehat{K}_{a}(\varphi\wedge\psi)\vee\widehat{K}_{a}(\psi\wedge\widehat{K}_{a}\varphi))\)
No branching to the right: \(\forall x,y,z,\text{if }xRy\text{ and }xRz,\text{then }yRz\text{ or }y=z\text{ or }zRy\) |

.3.2 |
\((\widehat{K}_{a}\varphi\wedge\widehat{K}_{a}K_{a}\psi)\rightarrow
K_{a}(\widehat{K}_{a}\varphi\vee\psi)\)
Semi-Euclidean: \(\forall x,y,z,\) if \(xRy\) and \(xRz\), then \(zRx\) or \(yRz\). |

.4 | \((\varphi\wedge\widehat{K}_{a}K_{a}\varphi)\rightarrow
K_{a}\varphi\)
Unknown to authors: Not applicable |

Table 1. Epistemic Principles and their frame conditions.

Adding epistemic principles as axioms to the basic minimal normal
modal logic **K** yields new, normal modal logics. A
selection is:

K |
\(\{\text{K}\}\) |

T |
\(\{\text{K},\text{T}\}\) |

D |
\(\{\text{K},\text{D}\}\) |

KD4 |
\(\{\text{K},\text{D},\text{4}\}\) |

KD45 |
\(\{\text{K},\text{D},\text{4},\text{5}\}\) |

S4 |
\(\{\text{K},\text{T},\text{4}\}\) |

S4.2 |
\(\{\text{K},\text{T},\text{4},\text{.2}\}\) |

S4.3 |
\(\{\text{K},\text{T},\text{4},\text{.3}\}\) |

S4.4 |
\(\{\text{K},\text{T},\text{4},\text{.4}\}\) |

S5 |
\(\{\text{K},\text{T},\text{5}\}\) |

Table 2. Logic names and axioms

Different axiomatic specifications may produce the same logic. Notice,
e.g., that the table’s axiomatic specification
\(\{\text{K},\text{T},\text{5}\}\) of **S5** does not
match that given in the definition preceding Theorem 1,
\(\{\text{K},\text{T},\text{B},\text{4}\}\). Note also, there is more
than one axiomatization of **S5**: the axioms
\(\{\text{K},\text{T},\text{5}\}\),
\(\{\text{K},\text{T},\text{B},\text{4}\}\),
\(\{\text{K},\text{D},\text{B},\text{4}\}\) and
\(\{\text{K},\text{D},\text{B},\text{5}\}\) all give the
**S5** logic (cf., e.g., Chellas 1980). An often seen
variant is \(\{\text{K},\text{T},\text{4},\text{5}\}\). However, it is
redundant to add it as all its instances can be proven from K, T and
5. But as both 4 and 5 capture important epistemic principles (see
Section 2.6),
4 is often sometimes included for the sake of philosophical
transparency. For more equivalences between modal logics, see, e.g.,
the entry on
modal logic
or Chellas (1980) or Blackburn, de Rijke, and Venema (2001).

Logics may be stronger or weaker than each other, and knowing the
frame properties of their axioms may help us to understand their
relationship. For example, as 4 is derivable from
\(\{\text{K},\text{T},\text{5}\}\), all the theorems of
**S4** are derivable in **S5**.
**S5** is thus *at least as strong* as
**S4**. In fact, **S5** is also *strictly
stronger*: It can prove things which **S4**
cannot.

That **S5** may be axiomatized both by
\(\{\text{K},\text{T},\text{B},\text{4}\}\) and
\(\{\text{K},\text{T},\text{5}\}\) may be seen through the frame
properties of the axioms: every reflexive and euclidean relation (T
and 5) is an equivalence relation (T, B, and 4). This also shows the
redundancy of 4: If one has assumed a relation reflexive and
euclidean, then it adds nothing new to additionally assume it to be
transitive. In general, having an understanding of the interplay
between relational properties is of great aid in seeing relationships
between modal logics. For example, noticing that every reflexive
relation is also serial means that all formulas valid on the class of
serial models are also valid on the class of reflexive models. Hence,
every theorem of **D** is thus a theorem of
**T**. Hence **T** is at least as strong as
**D** (i.e., \(\textbf{D}\subseteq\textbf{T}\)). That
**T** is also strictly stronger (not
\(\textbf{T}\subseteq\textbf{D}\)) can be shown by finding a serial,
non-reflexive model which does not satisfy some theorem of
**T** (for example \(K_{a}p\rightarrow p\)).

### 2.6 Principles of Knowledge and Belief

With the formal background of epistemic logic in place, it is straightforward to slightly vary the framework in order to accommodate the concept of belief. Return to the language \(\mathcal{L}_{KB}\) of both knowledge and belief:

\[\varphi:=p\mid \neg\varphi\mid (\varphi\wedge\varphi)\mid K_{a}\psi\mid B_{a}\psi,\text{ for } p\in \textit{Atom}.\]To interpret knowledge and belief formulas together in pointed Kripke models, all that is needed is an additional relation between possible worlds:

**Definition:** A ** pointed Kripke
model** for \(\mathcal{L}_{KB}\) is a tuple
\((M,w)=(W,R_{K},R_{B},V,w)\) where

*W*is a non-empty set of possible worlds,- \(R_{K}\) and \(R_{B}\) are a binary relations on
*W*, - \(V\colon \textit{Atom}\longrightarrow\mathcal{P}(W)\) is a valuation, and
- \(w\in W\).

\(R_{K}\) is the relation for the knowledge operator and \(R_{B}\) the relation for the belief operator. The definition makes no further assumptions about their properties. In the figure below we provide an illustration, where the arrows are labeled in accordance with the relation they correspond to. The reflexive loop at \(w_{3}\) is a label indicating that it belongs to both relations, i.e., \((w_{3},w_{3})\in R_{K}\) and \((w_{3},w_{3})\in R_{B}\).

The satisfaction relation is defined as above, but with the obvious changes for knowledge and belief:

\((M,w)\vDash K_{a}\varphi\) iff \((M,w')\vDash\varphi\) for all \(w'\in W\) such that \(wR_{K}w'\).

\((M,w)\vDash B_{a}\varphi\) iff \((M,w')\vDash\varphi\) for all \(w'\in W\) such that \(wR_{B}w'\).

The indistinguishability interpretation puts very strong requirements on the accessibility relation for knowledge. These have now been stripped away and so has any commitment to the principles T, B, D, 4 and 5. Taking Kripke models as basic semantics, we are still committed to K, though this principle is not unproblematic as we shall see below in our discussion of the problem of logical omniscience.

Of the principles from Table 1, T, D, B, 4 and 5 have been discussed most extensively in the literature on epistemic logic, both as principles for knowledge and as principles for belief. The principle T for knowledge

\[ K_{a}\varphi\rightarrow\varphi \]
is broadly accepted. Knowledge is commonly taken to be
*veridical*only true proposition can be known. For, e.g.,
Hintikka (1962) and Fagin et al. (1995), the failure of T for belief
is the defining difference between the two notions.

Though belief is not commonly taken to be veridical, believes are
typically taken to be *consistent*. I.e., agents are taken to
*never* believe the contradiction that is, any formula
equivalent with \((p\wedge\neg p)\) or \(\bot\), for short. That
believes should be consistent is then captured by the principle

The principle \(\neg B_{a}\bot\) is, on Kripke models, equivalent with
the principle D, \(B_{a}\varphi\rightarrow\widehat{B}_{a}\varphi\).
Hence the validity of \(\neg B_{a}\bot\) requires serial frames.
Witness, e.g., its failure in \(w_{1}\) above: As there are no worlds
accessible through \(R_{B}\), *all* accessible worlds satisfy
\(\bot\). Hence \(w_{1}\) satisfies \(B_{a}\bot\), violating
consistency. Notice also that \(\neg B_{a}\bot\) may be re-written to
\(\widehat{B}_{a}\top\), which is true at a world just in case some
world is accessible through \(R_{B}\). Its validity thus ensures
seriality.

Notice that the veridicality of knowledge ensures its consistency: Any reflexive frame is automatically serial. Hence accepting \(K_{a}\varphi\rightarrow\varphi\) implies accepting \(\neg K_{a}\bot\).

Of the principles D, 4 and 5, the two latter have received far the
most attention, both for knowledge and for belief. They are commonly
interpreted as governing of *principled access* to own mental
states. The 4 principles

are often referred to as *principles of positive
introspection*, or for knowledge the *‘KK’
principle*. Both principles are deemed acceptable by, e.g.,
Hintikka (1962) on grounds *different* from introspection. He
argues based on an autoepistemic analysis of knowledge, using a
non-Kripkean possible worlds semantics called *model systems*.
Hintikka holds that when an agent commits to knowing \(\varphi\), the
agent commits to holding the same attitude no matter what new
information the agent will encounter in future. This entails that in
all the agent’s epistemic alternatives for Hintikka, all the
model sets (partial descriptions of possible worlds) where the agent
knows at least as much they now do the agent still knows \(\varphi\).
As \(K_{a}\varphi\) thus holds in all the agent’s epistemic
alternatives, Hintikka concludes that \(K_{a}K_{a}\varphi\). Likewise
Hintikka endorses 4 for belief, but Lenzen raises objections (Lenzen
1978: ch. 4).

Williamson argues against the general acceptability of the principle
(Williamson 2000: ch. 5) for a concept of knowledge based on slightly
inexact observations, a so-called *margin of error principle*
(see, e.g., Aucher 2014 for a short summary).

The 5 principles

\[ \begin{align} \neg K_{a}\varphi &\rightarrow K_{a}\neg K_{a}\varphi\\ \neg B_{a}\varphi &\rightarrow B_{a}\neg B_{a}\varphi\\ \end{align} \]
are often referred to as *principles of negative
introspection*. Negative introspection is quite controversial as
it poses very high demands on knowledge and belief. The schema 5 may
be seen as a *closed world assumption* (Hendricks 2005): The
agent has complete overview of all the possible worlds and own
information. If \(\neg\psi\) is considered possible
(\(\widehat{K}_{a}\neg\psi\), i.e., \(\neg K_{a}\psi\)), then the
agent knows it is considered possible (\(K_{a}\neg K_{a}\psi\)). Such
a closed world assumption is natural when constructing hyper-rational
agents in, e.g., computer science or game theory, where the agents are
assumed to reason as hard as logically possible about their own
information when making decisions.

Arguing against 5 is Hintikka (1962), using his conception of epistemic alternatives. Having accepted T for knowledge, 5 stands or falls with the assumption of a symmetric accessibility relation. But, Hintikka argues, the accessibility relation is not symmetric: If the agent possess some amount of information at model set \(s_{1}\), then the model set \(s_{2}\) where the agent has learned something more will be an epistemic alternative to \(s_{1}\). But \(s_{1}\) will not be an epistemic alternative to \(s_{2}\), because in \(s_{1}\), the agent does by hypothesis not know as much as it does in \(s_{2}\). Hence the relation is not symmetric, so 5 is not a principle of knowledge, on Hintikka’s account.

Given Hintikka’s non-standard semantics, it is a bit difficult
to pin down whether he would accept a normal modal logic as the logics
of knowledge and belief, but if so, then **S4** and
**KD4** would be the closest candidates (see Hendricks
& Rendsvig 2018 for this point). By contrast, for knowledge von
Kutschera argued for **S4.4** (1976), Lenzen suggested
**S4.2** (1978), van der Hoek argued for
**S4.3** (1993), and Fagin, Halpern, Moses, and Vardi
(1995) and many others use **S5** for knowledge and
**KD45** for belief.

Beyond principles governing knowledge and principles governing belief, one may also consider principles governing the interplay between knowledge and belief. Three principles of interest are

\[\begin{align} \tag*{KB1} K_{a}\varphi & \rightarrow B_{a}\varphi\\ \tag*{KB2} B_{a}\varphi & \rightarrow K_{a}B_{a}\varphi\\ \tag*{KB3} B_{a}\varphi & \rightarrow B_{a}K_{a}\varphi\\ \end{align} \]
The principles KB1 and KB2 were introduced by Hintikka, who endorses
both Hintikka (1962) noting that Plato is also committed to KB1 in
*Theatetus*. The first principle, KB1, captures the intuition
that knowledge is a stronger notion than belief. The second like 4 and
5captures the idea that one has privileged access to one’s own
beliefs. The third, stemming from Lenzen (1978), captures the notion
that beliefs are held with some kind of conviction: if something is
believed, it is believed to be known.

Though the interaction principles KB1KB3 may look innocent on their own, they may lead to counterintuitive conclusions when combined with specific logics of knowledge and belief. First, Voorbraak (1993) shows that combining 5 for knowledge and D for belief with KB1, implies that

\[B_{a}K_{a}\varphi\rightarrow K_{a}\varphi\]is a theorem of the resulting logic. Assuming that knowledge is truthful, this theorem entails that agents cannot believe to know something which happens to be false.

If additionally KB3 is added, the notions of knowledge and belief
*collapse.* I.e., it may be proven that
\(B_{a}\varphi\rightarrow K_{a}\varphi\), which, in combination with
KB1 entails that

Hence, the two notions have collapsed to one. This was stated in 1986, by Kraus and Lehmann.

If one is not interested in knowledge and belief collapsing, one must
thus give something up: One cannot have both 5 for knowledge, D for
belief and KB1 and KB3 governing their interaction. Again, results
concerning correspondence between principles and relation properties
may assist: In 1993, van der Hoek showed based on a semantic analysis
that where the four principles are jointly sufficient for collapse,
*no subset of them is, too*. Giving up any one principle will
thus eliminate the collapse. Weakening KB1 to hold only for non-modal
formulas is also sufficient to avoid collapse (cf. Halpern 1996).

For more on epistemic interaction principles, the principles .2, .3,
.3.2. and .4, and relations to so-called *conditional beliefs*,
see Aucher (2014). For an introduction to conditional beliefs and
relations to several other types of knowledge from the philosophical
literature, see Baltag and Smets (2008). The latter also includes
discussion concerning the interdefinability of various notions, as
does Halpern, Samet, and Segev (2009) for knowledge and
(non-conditional) belief.

## 3. Knowledge in Groups

We human beings are preoccupied with the epistemic states of other agents. In ordinary life, we reason with varying degrees of success about what others know. We are especially concerned with what others know about us, and often specifically about what they know about what we know.

Does she know that I know where she buried the treasure?

Does she know that I know that she knows?

And so on.

Epistemic logic can reveal interesting epistemic features of systems involving groups of agents. In some cases, for example, emergent social phenomena depend on agents reasoning in particular ways about the knowledge and beliefs of other agents. As we have seen, traditional systems of epistemic logic applied only to single-agent cases. However, they can be extended to groups or multi-agent systems in a relatively straightforward manner.

As David Lewis noted in his book *Convention* (1969) many
prominent features of social life depend on agents assuming that the
rules of some practice are matters of *common knowledge*. For
example, drivers know that a red traffic light indicates that they
should stop at an intersection. However, for the convention of traffic
lights to be in place at all, it is first necessary that drivers must
also know that other drivers know that *red* means
*stop*. In addition, drivers must also know that everyone knows
that everyone knows that …. The conventional role of traffic
lights relies on all drivers knowing that all drivers know the rule,
that the rule is a piece of
common knowledge.

A variety of norms, social and linguistic practices, agent
interactions and games presuppose common knowledge, first formalized
by Aumann (1976) and with earliest epistemic logical treatments by
Lehmann (1984) and by Halpern and Moses (1984). In order to see how
epistemic logic sheds light on these phenomena, it is necessary to
introduce a little more formalism. Following the standard treatment
(see, e.g., Fagin et al. 1995), we can syntactically augment the
language of propositional logic with *n* knowledge operators, one
for each agent involved in the group of agents under consideration.
The primary difference between the semantics given for a mono-agent
and a multi-agent semantics is roughly that *n* accessibility
relations are introduced. A modal system for *n* agents is
obtained by joining together *n* modal logics where for
simplicity it may be assumed that the agents are homogenous in the
sense that they may all be described by the same logical system. An
epistemic logic for *n* agents consists of *n* copies of a
certain modal logic. In such an extended epistemic logic it is
possible to express that some agent in the group knows a certain fact
that an agent knows that another agent knows a fact etc. It is
possible to develop the logic even further: Not only may an agent know
that another agent knows a fact, but they may all know this fact
simultaneously.

### 3.1 Multi-Agent Languages and Models

To represent knowledge for a set \(\mathcal{A}\) of *n* agents,
first let’s stipulate a language. Let \(\mathcal{L}_{Kn}\) be
given by the *Backus-Naur form*

To represent knowledge for all *n* agents jointly in pointed
Kripke models, all that is needed is to add suitably many
relations:

**Definition:** A ** pointed Kripke
model** for \(\mathcal{L}_{Kn}\) is a tuple
\((M,w)=(W,\{R_{i}\}_{i\in\mathcal{A}},V,w)\) where

*W*is a non-empty set of possible worlds,- For every \(i\in\mathcal{A}\), \(R_{i}\) is a binary relation on
*W*, - \(V\colon \textit{Atom}\longrightarrow\mathcal{P}(W)\) is a valuation, and
- \(w\in W\).

To also incorporate beliefs, simply apply the same move as in the single agent case: augment the language and let there be two relations for each agent.

The definition uses a family of relations
\(\{R_{i}\}_{i\in\mathcal{A}}\). In the literature, the same is
denoted \((W,R_{i},V,w)_{i\in\mathcal{A}}\). Alternatively, *R*
is taken to be a function sending agents to relations, i.e.,
\(R:\mathcal{A\rightarrow}\mathcal{P}(W\times W)\). Then for each
\(i\in\mathcal{A}\), \(R(i)\) is a relation on *W*, often denoted
\(R_{i}\). These are stylistic choices.

When considering only a single agent, it is typically not relevant to
include more worlds in *W* than there are possible valuations of
atoms. In multi-agent cases, this is not the case: to express the
different forms of available higher-order knowledge, many copies of
“the same” world are needed. Let us exemplify for
\(\mathcal{A}=\{a,b\}\), \(\textit{Atom}=\{p\}\) and each
\(R_{i},i\in\mathcal{A},\) an equivalence relation. Let us represent
that both *a* and *b* know *p*, but *b* does not
know that *a* knows *p* , i.e., \(K_{a}p\wedge
K_{b}p\wedge\neg K_{b}K_{a}p\). Then we need three worlds:

If we try to let \(w_{1}\) play the role of \(w_{2}\), then *a*
would lose knowledge in *p*: both *p* worlds are needed. In
general, if *W* is assumed to have any fixed, finite size, there
will be some higher-order information formula that cannot be satisfied
in it.

### 3.2 Notions of Group Knowledge

Multi-agent systems are interesting for other reasons than to
represent higher-order information. The individual agents’
information may also be pooled to capture what the agents know
jointly, as group knowledge (see Baltag, Boddy, & Smets 2018 for a
recent discussion). A standard notion is this style is *distributed
knowledge*: The knowledge the group *would have* if the
agents share all their individual knowledge. To represent it, augment
the language \(\mathcal{L}_{Kn}\) with operators

to make \(D_{G}\varphi\) a well-formed formula. Where
\(G\subseteq\mathcal{A}\) is a group of agents, the formula
\(D_{G}\varphi\) reads that it is *distributed knowledge in the
group G that \(\varphi\)*.

To evaluate \(D_{G}\varphi\), we define a new relation from those already present in the model. The idea behind the definition is that if some one agent has eliminated a world as an epistemic alternative, then so will the group. Define the relation as the intersection of the individual agents’ relations:

\[R_{G}^{D}=\bigcap_{i\in G}R_{i}\]In the three state model, \(R_{G}^{D}\) contains only the three loops. To evaluate a distributed knowledge formula, use the same form as for other modal operators:

\[(M,w)\vDash D_{G}\varphi\text{ iff }(M,w')\vDash\varphi\text{ for all }w'\in W\text{ such that }wR_{G}^{D}w'.\]
It may be the case that some very knowing agent knows all that is
distributed knowledge in *G*, but it is not guaranteed. To
capture that all the agents know \(\varphi\), we could use the
conjunction of the formulas \(K_{i}\varphi\) for \(\in\mathcal{A}\),
i.e., \(\bigwedge_{i\in\mathcal{A}}K_{i}\varphi\). This is a
well-defined formula if \(\mathcal{A}\) is finite (which it typically
is). If \(\mathcal{A}\) is not finite, then
\(\bigwedge_{i\in\mathcal{A}}K_{i}\varphi\) is not a formula in
\(\mathcal{L}_{Kn}\), as it has only finite conjunctions. As a
shorthand for \(\bigwedge_{i\in\mathcal{A}}K_{i}\varphi\), it is
standard to introduce the *everybody knows* operator,
\(E_{G}\):

In the three world model, \(K_{a}p\wedge K_{b}p\), so \(E_{\{a,b\}}p\).

That everybody knows something does not mean that this knowledge is shared between the members of the group. The three world model exemplifies this: Though \(E_{\{a,b\}}p\), it also the case that \(\neg K_{b}E_{\{a,b\}}p\).

To capture that there is no uncertainty in the group about \(\varphi\)
nor *any higher-order* uncertainty about \(\varphi\) being
known by all agents, no formula in the language \(\mathcal{L}_{Kn}\)
is enough. Consider the formula

where \(E_{G}^{k}\) is short for *k* iterations of the \(E_{G}\)
operator. Then for no natural number *k* will the formula
\(E_{G}^{k}\varphi\) be enough: it could be the case that *b*
doesn’t know it! To rectify this situation, one could try

but this is not a formula as \(\mathcal{L}_{Kn}\) only contains finite conjunctions.

Hence, though the \(E_{G}\) operator is definable in the language
\(\mathcal{L}_{Kn}\), a suitable notion of *common knowledge*
is not. For that, we again need to define a new relation on our model.
This time, we are interested in capturing that nobody considers
\(\varphi\) epistemically possible *anywhere*. To build the
relation, we therefore first take the union the relations of all the
agents in *G*, but this is not quite enough: to use the standard
modal semantic clause, we must also be able to reach all of the worlds
in this relation *in a single step*. Hence, let

where \((\cdotp)^{*}\) is the operation of taking the *transitive
closure.* If *R* is a relation, then \((R)^{*}\) is *R*
plus all the pairs missing to make *R* a transitive relation.
Consider the three world model: With the relation
\(\bigcup_{i\in\{a,b\}}R_{i}\), we can reach \(w_{3}\) from \(w_{1}\)
in two steps, stopping over at \(w_{2}\). With
\((\bigcup_{i\in\{a,b\}}R_{i})^{*}\), \(w_{3}\) is reachable in one
step: By the newly added transitive link from \(w_{1}\) to
\(w_{3}\).

To represent common knowledge, augment the *Backus-Naur form*
of \(\mathcal{L}_{Kn}\) with operators

to make \(C_{G}\varphi\) a well-formed formula. Evaluate such formulas by the semantic clause

\[(M,w)\vDash C_{G}\varphi\text{ iff }(M,w')\vDash\varphi\text{ for all }w'\in W\text{ such that }wR_{G}^{C}w'.\]
Varying the properties of the accessibility relations
\(R_{1},R_{2},\ldots,R_{n}\), as described above results in different
epistemic logics. For instance system **K** with common
knowledge is determined by all frames, while system
**S4** with common knowledge is determined by all
reflexive and transitive frames. Similar results can be obtained for
the remaining epistemic logics (Fagin et al. 1995). For more, consult
the entry on common knowledge.

## 4. Logical Omniscience

The principal complaint against the approach taken by epistemic logicians is that it is committed to an excessively idealized picture of human reasoning. Critics have worried that the relational semantics of epistemic logic commits one to a closure property for an agent’s knowledge that is implausibly strong given actual human reasoning abilities. The closure properties give rise to what has come to be called the problem of logical omniscience:

Whenever an agent *c* knows all of the formulas in a set
\(\Gamma\) and *A* follows logically from \(\Gamma\),
then *c* also knows *A*.

In particular, *c* knows all theorems (letting
\(\Gamma=\emptyset\)), and knows all the logical consequences of any
formula that the agent knows (letting \(\Gamma\) consist of a single
formula). The concern here is that finite agents are constrained by
limits on their cognitive capacities and reasoning abilities.
The account of knowledge and belief that epistemic logic seems
committed to involves superhuman abilities like knowing all the
tautologies. Thus, the concern is that epistemic logic is simply
unsuited to capturing actual knowledge and belief as these notions
figure in ordinary human life.

Hintikka recognized a discrepancy between the rules of epistemic logic
and the way the verb “to know” is ordinarily used already
in the early pages of *Knowledge and Belief*. He pointed out
that

it is clearly inadmissible to infer “he knows that

q” from “he knows thatp” solely on the basis thatqfollows logically fromp, for the person in question may fail to see thatpentailsq, particularly ifpandqare relatively complicated statements. (1962: 30-31)

Hintikka’s first reaction to what came to be called the problem
of logical omniscience was to see the discrepancy between ordinary
usage of terms like “consistency” and formal treatments of
knowledge as indicating a problem with our ordinary terminology. If a
person knows the axioms of a mathematical theory but is unable to
state the distant consequences of the theory, Hintikka denied that it
is appropriate to call that person inconsistent. In ordinary
human affairs, Hintikka claimed, the charge of inconsistency when
directed towards an agent has the connotation of being irrational or
dishonest. Thus, from Hintikka’s perspective we should
choose some other term to capture the situation of someone who is
rational and amenable to persuasion or correction but not logically
omniscient. Non-omniscient, rational agents can be in a position to
say that “I know that *p* but I don’t know whether
*q*” even in case *q* can *p*. He then suggests
that *q* should be regarded as *defensible* given the
agent’s knowledge and the denial of *q* should be regarded
as *indefensible*. This choice of terminology was criticized
insofar as it attaches the pejorative *indefensible* to some
set of proposition, even though the fault actually lies in the
agent’s cognitive capacities (Chisholm 1963; Hocutt 1972; Jago
2007).

Hintikka’s early epistemic logic can be understood as a way of reasoning about what is implicit in an agent’s knowledge even in cases where the agent itself is unable to determine what is implicit. Such an approach risks being excessively idealized and its relevance for understanding human epistemic circumstances can be challenged on these grounds.

Few philosophers were satisfied with Hintikka’s attempt to
revise our ordinary use of the term “consistent” as he
presented it in *Knowledge and Belief. *However, he and
others soon provided more popular ways of dealing with logical
omniscience. In the 1970s responses to the problem of logical
omniscience introduced semantical entities that explain why the agent
appears to be, but in fact is not really guilty of logical
omniscience. Hintikka called these entities “impossible possible
worlds” (1979; see also the entry on
impossible worlds
and Jago 2014). The basic idea is that an agent may mistakenly count
among the worlds consistent with its knowledge, some worlds containing
logical contradictions. The mistake is simply a product of the
agent’s limited resources; the agent may not be in a position to
detect the contradiction and may erroneously count them as genuine
possibilities. In some respects, this approach can be understood as an
extension of the aforementioned response to logical omniscience that
Hintikka had already outlined in *Knowledge and Belief.*

In the same spirit, entities called “seemingly possible” worlds are introduced by Rantala (1975) in his urn-model analysis of logical omniscience. Allowing impossible possible worlds or seemingly possible worlds in which the semantic valuation of the formulas is arbitrary to a certain extent provides a way of making the appearance of logical omniscience less threatening. After all, on any realistic account of epistemic agency, the agent is likely to consider (albeit inadvertently) worlds in which the laws of logic do not hold. Since no real epistemic principles hold broadly enough to encompass impossible and seemingly possible worlds, some conditions must be applied to epistemic models such that they cohere with epistemic principles (for criticism of this approach see Jago 2007: 336-337).

Alternatively to designing logics in which the knowledge operators do
not exhibit logical omniscience, *awareness logic* offers an
alternative: Change the interpretation of \(K_{a}\varphi\) from
“*a* knows that \(\varphi\)” to “*a*
*implicitly* knows that \(\varphi\)” and take
*explicit* knowledge that \(\varphi\) to be implicit knowledge
that \(\varphi\) *and* awareness of \(\varphi\). With awareness
not closed under logical consequence, such a move allows for notion of
explicit knowledge not logically omniscient. As agents neither have to
compute their implicit knowledge nor can they be held responsible for
answering queries based on it, logical omniscience is problematic only
for explicit knowledge, the *problem* of logical omniscience is
thus averted. Though logical omniscience is an epistemological
condition for implicit knowledge, the agent itself may actually fail
to realize this condition. For more on awareness logic, see, e.g., the
seminal Fagin & Halpern (1987) or Velazquez-Quesada (2011) and
Schipper (2015) for overviews.

Debates about the various kinds of idealization involved in epistemic logic are ongoing in both philosophical and interdisciplinary contexts.

## Bibliography

- Arló-Costa, Horacio, Vincent F. Hendricks, and Johan van
Benthem (eds.), 2016,
*Readings in Formal Epistemology*, Cham: Springer International Publishing. doi:10.1007/978-3-319-20451-2 - Artemov, Sergei and Elena Nogina, 2005, “Introducing
Justification into Epistemic Logic”,
*Journal of Logic and Computation*, 15(6): 1059–1073. doi:10.1093/logcom/exi053 - Aucher, Guillaume, 2014, “Principles of Knowledge, Belief
and Conditional Belief”, in
*Interdisciplinary Works in Logic, Epistemology, Psychology and Linguistics: Dialogue, Rationality, and Formalism*, Manuel Rebuschi, Martine Batt, Gerhard Heinzmann, Franck Lihoreau, Michel Musiol, and Alain Trognon (eds.), Cham: Springer International Publishing, 97–134. doi:10.1007/978-3-319-03044-9_5 - Aumann, Robert J., 1976, “Agreeing to Disagree”,
*The Annals of Statistics*, 4(6): 1236–1239. Reprinted in Arló-Costa, Hendricks, and van Benthem 2016: 859–862. doi:10.1214/aos/1176343654, doi:10.1007/978-3-319-20451-2_40 - Baltag, A., R. Boddy, and S. Smets, 2018, “Group Knowledge in Interrogative Epistemology”, in van Ditmarsch and Sandu 2018: 131–164. doi:10.1007/978-3-319-62864-6_5
- Baltag, Alexandru and Sonja Smets, 2008, “A Qualitative
Theory of Dynamic Interactive Belief Revision”, in
*Logic and the Foundations of Game and Decision Theory (LOFT 7)*, G. Bonanno, W. van der Hoek, and M. Wooldridge (eds.) (Texts in Logic and Games, Vol. 3), Amsterdam: Amsterdam University Press, 9–58. - Benthem, Johan van, 2006, “Epistemic Logic and Epistemology:
The State of Their Affairs”,
*Philosophical Studies*, 128(1): 49–76. doi:10.1007/s11098-005-4052-0 - –––, 2011,
*Logical Dynamics of Information and Interaction*, Cambridge: Cambridge University Press. doi:10.1017/CBO9780511974533 - Blackburn, Patrick, Maarten de Rijke, and Yde Venema, 2001,
*Modal Logic*, Cambridge: Cambridge University Press. doi:10.1017/CBO9781107050884 - Boër, Steven E. and William G. Lycan, 1986,
*Knowing Who*, Cambridge, MA: MIT Press. - Boh, Ivan, 1993,
*Epistemic Logic in the Later Middle Ages*, (Topics in Medieval Philosophy), London/New York: Routledge. - Chellas, Brian F., 1980,
*Modal Logic: An Introduction*, Cambridge: Cambridge University Press. - Chisholm, Roderick M., 1963, “The Logic of Knowing”,
*The Journal of Philosophy*, 60(25): 773–795. doi:10.2307/2022834 - Ditmarsch, Hans van, Joseph Y. Halpern, Wiebe van der Hoek, and
Barteld Kooi (eds.), 2015,
*Handbook of Epistemic Logic*, London: College Publications. - Ditmarsch, Hans van, Wiebe van der Hoek, and Barteld Kooi, 2007,
*Dynamic Epistemic Logic*, Dordrecht: Springer Netherlands. doi:10.1007/978-1-4020-5839-4 - Ditmarsch, Hans van and Gabriel Sandu (eds.), 2018,
*Jaakko Hintikka on Knowledge and Game-Theoretical Semantics*, (Outstanding Contributions to Logic, 12), Cham: Springer International Publishing. doi:10.1007/978-3-319-62864-6 - Fagin, Ronald and Joseph Y. Halpern, 1987, “Belief,
Awareness, and Limited Reasoning”,
*Artificial Intelligence*, 34(1): 39–76. doi:10.1016/0004-3702(87)90003-8 - Fagin, Ronald, Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi,
1995,
*Reasoning About Knowledge*, Cambridge, MA: The MIT Press. - Gochet, Paul and Pascal Gribomont, 2006, “Epistemic
Logic”, in
*Handbook of the History of Logic, 7*, Amsterdam: Elsevier, 99–195. doi:10.1016/S1874-5857(06)80028-2 - Halpern, Joseph Y., 1996, “Should Knowledge Entail
Belief?”,
*Journal of Philosophical Logic*, 25(5): 483–494. doi:10.1007/BF00257382 - Halpern, Joseph Y., Dov Samet, and Ella Segev, 2009,
“Defining Knowledge in Terms of Belief: The Modal Logic
Perspective”,
*The Review of Symbolic Logic*, 2(3): 469–487. doi:10.1017/S1755020309990141 - Halpern, Joseph Y. and Yoram Moses, 1984, “Knowledge and
Common Knowledge in a Distributed Environment”, in
*Proceedings of the Third Annual ACM Symposium on Principles of Distributed Computing (PODC ’84)*, Vancouver, British Columbia, Canada, ACM Press, 50–61. doi:10.1145/800222.806735 - Hendricks, Vincent F., 2005,
*Mainstream and Formal Epistemology*, Cambridge: Cambridge University Press. doi:10.1017/CBO9780511616150 - Hendricks, Vincent F. and Rasmus K. Rendsvig, 2018, “Hintikka’s Knowledge and Belief in Flux”, in van Ditmarsch and Sandu 2018: 317–337. doi:10.1007/978-3-319-62864-6_13
- Hendricks, Vincent F. and John Symons, 2006, “Where’s the
Bridge? Epistemology and Epistemic Logic”,
*Philosophical Studies*, 128(1): 137–167. doi:10.1007/s11098-005-4060-0 - Hintikka, Jaakko, 1962 [2005],
*Knowledge and Belief: An Introduction to the Logic of the Two Notions*, second edition, Vincent F. Hendriks and John Symons (eds.), (Texts in Philosophy, 1), London: College Publications. - –––, 1969, “Semantics for Propositional
Attitudes”, in
*Philosophical Logic*, J. W. Davis, D. J. Hockney, and W. K. Wilson (eds.), Dordrecht: Springer Netherlands, 21–45. doi:10.1007/978-94-010-9614-0_2 - –––, 1978, “Impossible Possible Worlds
Vindicated”, in
*Game-Theoretical Semantics*, Esa Saarinen (ed.) (SLAP 5), Dordrecht: Springer Netherlands, 367–379. doi:10.1007/978-1-4020-4108-2_13 - –––, 2007, “Epistemology without Knowledge
and without Belief”, in
*Socratic Epistemology: Explorations of Knowledge-Seeking by Questioning*, Cambridge: Cambridge University Press, 11–37. doi:10.1017/CBO9780511619298.002 - Hintikka, Jaakko and John Symons, 2003, “Systems of Visual
Identification in Neuroscience: Lessons from Epistemic Logic”,
*Philosophy of Science*, 70(1): 89–104. doi:10.1086/367871 - Hocutt, Max O., 1972, “Is Epistemic Logic Possible?”,
*Notre Dame Journal of Formal Logic*, 13(4): 433–453. doi:10.1305/ndjfl/1093890705 - Hoek, Wiebe van der, 1993, “Systems for Knowledge and
Belief”,
*Journal of Logic and Computation*, 3(2): 173–195. doi:10.1093/logcom/3.2.173 - Holliday, Wesley H., 2018, “Epistemic Logic and
Epistemology”, in
*Introduction to Formal Philosophy*, Sven Ove Hansson and Vincent F. Hendricks (eds.), Cham: Springer International Publishing, 351–369. doi:10.1007/978-3-319-77434-3_17 - Jago, Mark, 2007, “Hintikka and Cresswell on Logical
Omniscience”,
*Logic and Logical Philosophy*, 15(4): 325–354. doi:10.12775/LLP.2006.019 - –––, 2014,
*The Impossible: An Essay on Hyperintensionality*, Oxford: Oxford University Press. doi:10.1093/acprof:oso/9780198709008.001.0001 - Knuuttila, Simo, 1993,
*Modalities in Medieval Philosophy*, (Topics in Medieval Philosophy), New York: Routledge. - Kraus, Sarit and Daniel Lehmann, 1986, “Knowledge, Belief
and Time”, in
*Automata, Languages and Programming*, Laurent Kott (ed.), Berlin, Heidelberg: Springer Berlin Heidelberg, 186–195. - Kutschera, Franz von, 1976,
*Einführung in Die Intensionale Semantik*, (De Gruyter Studienbuch : Grundlagen Der Kommunikation), Berlin/New York: De Gruyter. - Lehmann, Daniel, 1984, “Knowledge, Common Knowledge and
Related Puzzles (Extended Summary)”,
*Proceedings of the Third Annual ACM Symposium on Principles of Distributed Computing (PODC ’84)*, 62–67. doi:10.1145/800222.806736 - Lenzen, Wolfgang, 1978,
*Recent Work in Epistemic Logic*, (Acta Philosophica Fennica, 30), Amsterdam: North Holland Publishing Company. - –––, 1980,
*Glauben, Wissen Und Wahrscheinlichkeit: Systeme Der Epistemischen Logik*, (Library of Exact Philosophy, 12), Wien: Springer. - Lewis, David K., 1969,
*Convention: A Philosophical Study*, Cambridge, MA: Harvard University Press. - Meyer, John-Jules Ch, 2001, “Epistemic Logic”, in
*The Blackwell Guide to Philosophical Logic*, Lou Goble (ed.), Oxford: John Wiley & Sons, 183–202. - Meyer, John-Jules Ch. and Wiebe van der Hoek, 1995,
*Epistemic Logic for AI and Computer Science*, (Cambridge Tracts in Theoretical Computer Science, 41), Cambridge: Cambridge University Press. - Rantala, Veikko, 1975, “Urn Models: A New Kind of
Non-Standard Model for First-Order Logic”,
*Journal of Philosophical Logic*, 4(4): 455–474. doi:10.1007/BF00558760 - Rendsvig, Rasmus K., 2012, “Modeling Semantic Competence: A
Critical Review of Frege’s Puzzle about Identity”, in
*New Directions in Logic, Language and Computation*, Daniel Lassiter and Marija Slavkovik (eds.), Berlin/Heidelberg: Springer Berlin Heidelberg, 140–157. doi:10.1007/978-3-642-31467-4_10 - Renne, Bryan, 2008, “Dynamic Epistemic Logic with Justification”, Ph.D. Thesis, New York: City University of New York.
- Schipper, Burkhard C., 2015, “Awareness”, in Ditmarsch et al. 2015: 77–146.
- Stalnaker, Robert, 2006, “On Logics of Knowledge and
Belief”,
*Philosophical Studies*, 128(1): 169–199. doi:10.1007/s11098-005-4062-y - Velazquez-Quesada Fernando Raymundo, 2011, “Small Steps in Dynamics of Information”, Ph.D. Thesis, Institute for Logic, Language and Computation, University of Amsterdam.
- Voorbraak, Franciscus Petrus Johannes Maria, 1993, “As Far as I Know: Epistemic Logic and Uncertainty”, Ph.D. Thesis, Department of Philosophy, Utrecht University.
- Wang, Yanjing, 2015, “A Logic of Knowing How”, in
*Logic, Rationality, and Interaction*, Wiebe van der Hoek, Wesley H. Holliday, and Wen-fang Wang (eds.), Berlin, Heidelberg: Springer Berlin Heidelberg, 392–405. doi:10.1007/978-3-662-48561-3_32 - –––, 2018, “Beyond Knowing That: A New Generation of Epistemic Logics”, in van Ditmarsch and Sandu 2018: 499–533. doi:10.1007/978-3-319-62864-6_21
- Williamson, Timothy, 2000,
*Knowledge and Its Limits*, Oxford: Oxford University Press. doi:10.1093/019925656X.001.0001 - Wright, Georg Henrik von, 1951,
*An Essay in Modal Logic*, (Studies in Logic and the Foundations of Mathematics), Amsterdam: North-Holland Publishing Company.

## Academic Tools

How to cite this entry. Preview the PDF version of this entry at the Friends of the SEP Society. Look up this entry topic at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers, with links to its database.

## Other Internet Resources

- Hintikka’s World, a graphical, pedagogical tool for learning about epistemic logic, higher-order reasoning and knowledge dynamics.
- Modal Logic Playground, a graphical interface for drawing and evaluating formulas of modal propositional logic.
- Hendricks, Vincent and John Symons, “Epistemic Logic”,
*Stanford Encyclopedia of Philosophy*(Spring 2019 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/spr2019/entries/logic-epistemic/>. [This was the previous entry on this topic in the*Stanford Encyclopedia of Philosophy*— see the version history.]