Abstract
It is well-known that in finite strategic games true common belief (or common knowledge) of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies. We establish a general theorem that deals with monotonic rationality notions and arbitrary strategic games and allows to strengthen the above result to arbitrary games, other rationality notions, and transfinite iterations of the elimination process. We also clarify what conclusions one can draw for the customary dominance notions that are not monotonic. The main tool is Tarski’s Fixpoint Theorem.
1. Introduction
1.1. Contributions
In this paper we provide an epistemic analysis of arbitrary strategic games based on possibility correspondences. We prove a general result that is concerned with monotonic program properties1 used by the players to select optimal strategies.
More specifically, given a belief model for the initial strategic game, denote by the property that each player i uses a property to select his strategy (‘each player i is -rational’). We establish in Section 3 the following general result:
Assume that each property is monotonic. The set of joint strategies that the players choose in the states in which is a true common belief is included in the set of joint strategies that remain after the iterated elimination of the strategies that for player i are not -optimal.
In general, transfinite iterations of the strategy elimination are possible. For some belief models the inclusion can be reversed.
This general result covers the usual notion of rationalizability in finite games and a ‘global’ version of the iterated elimination of strictly dominated strategies used in [] and studied for arbitrary games in []. It does not hold for the ‘global’ version of the iterated elimination of weakly dominated strategies. For the customary, ‘local’ version of the iterated elimination of strictly dominated strategies we justify in Section 4 the statement
for arbitrary games and transfinite iterations of the elimination process. Rationality refers here to the concept studied in []. We also show that the above general result yields a simple proof of the well-known version of the above result for finite games and strict dominance by a mixed strategy.true common belief (or common knowledge) of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies
The customary, local, version of strict dominance is non-monotonic, so the use of monotonic properties has allowed us to provide epistemic foundations for a non-monotonic property. However, weak dominance, another non-monotonic property, remains beyond the reach of this approach. In fact, we show that in the above statement we cannot replace strict dominance by weak dominance. A mathematical reason is that its global version is also non-monotonic, in contrast to strict dominance, the global version of which is monotonic. To provide epistemic foundations of weak dominance the only currently known approaches are [] based on lexicographic probability systems and [] based on a version of the ‘all I know’ modality.
1.2. Connections
The relevance of monotonicity in the context of epistemic analysis of finite strategic games has already been pointed out in []. The distinction between local and global properties is from [] and [].
To show that for some belief models an equality holds between the set of joint strategies chosen in the states in which is true common belief and the set of joint strategies that remain after the iterated elimination of the strategies that for player i are not -rational requires use of transfinite ordinals. This complements the findings of [] in which transfinite ordinals are used in a study of limited rationality, and [], where a two-player game is constructed for which the (the first infinite ordinal) and iterations of the rationalizability operator of [] differ.
In turn, [] show that arbitrary ordinals are necessary in the epistemic analysis of arbitrary strategic games based on partition spaces. Further, as shown in [], the global version of the iterated elimination of strictly dominated strategies, when used for arbitrary games, also requires transfinite iterations of the underlying operator.
Finally, [] invokes Tarski’s Fixpoint Theorem, in the context of what the author calls “general systems”, and uses this to prove that the set of rationalizable strategies in a finite non-cooperative game is the largest fixpoint of a certain operator. That operator coincides with the global version of the elimination of never-best-responses.
Some of the results presented here were initially reported in a different presentation, in [].
2. Preliminaries
2.1. Strategic Games
Given n players () by a strategic game (in short, a game) we mean a sequence where for all
- is the non-empty set of strategies available to player i,
- is the payoff function for the player i, so where is the set of real numbers.
We denote the strategies of player i by , possibly with some superscripts. We call the elements of joint strategies. Given a joint strategy s we denote the ith element of s by , write sometimes s as , and use the following standard notation:
- ,
- .
Given a finite non-empty set A we denote by the set of probability distributions over A and call any element of a mixed strategy of player i.
In the remainder of the paper we assume an initial strategic game
A restriction of H is a sequence such that for all . Some of s can be the empty set. We identify the restriction with H. We shall focus on the complete lattice that consists of the set of all restrictions of the game H ordered by the componentwise set inclusion:
So in this lattice H is the largest element in this lattice.
2.2. Possibility Correspondences
In this and the next subsection we essentially follow the survey of []. Fix a non-empty set Ω of states. By an event we mean a subset of Ω.
A possibility correspondence is a mapping from Ω to the powerset of Ω. We consider three properties of a possibility correspondence P:
- (i)
- for all ω, ,
- (ii)
- for all ω and , implies ,
- (iii)
- for all ω, .
If the possibility correspondence satisfies properties (i) and (ii), we call it a belief correspondence and if it satisfies properties (i)–(iii), we call it a knowledge correspondence.2 Note that each knowledge correspondence P yields a partition of Ω.
Assume now that each player i has at its disposal a possibility correspondence . Fix an event E. We define
by induction on
and finally
If all s are belief correspondences, we usually write B instead of □ and if all s are knowledge correspondences, we usually write K instead of □. When , we say that the event E is common belief in the state ω and when , we say that the event E is common knowledge in the state ω.
An event F is called evident if . That is, F is evident if for all we have for all . In what follows we shall use the following alternative characterizations of common belief and common knowledge based on evident events:
where or (see [], respectively Proposition 4 on page 180 and Proposition on page 174), and
([], page 1237).
2.3. Models for Games
We now relate these considerations to strategic games. Given a restriction of the initial game H, by a model for G we mean a set of states Ω together with a sequence of functions , where . We denote it by .
In what follows, given a function f and a subset E of its domain, we denote by the range of f on E and by the restriction of f to E.
By the standard model for G we mean the model in which
- , where
Given a (not necessarily standard) model for a restriction G and a sequence of events in (i.e., of subsets of Ω) we define
and call it the restriction of G to . When each equals E we write instead of .
Finally, we extend the notion of a model for a restriction G to a belief model for G by assuming that each player i has a belief correspondence on Ω. If each is a knowledge correspondence, we refer then to a knowledge model. We write each belief model as
2.4. Operators
Consider a fixed complete lattice with the largest element ⊤. In what follows we use ordinals and denote them by . Given a, possibly transfinite, sequence of elements of D we denote their join and meet respectively by and .
Let T be an operator on , i.e., .
- We call T monotonic if for all , implies , and contracting if for all G, .
- We say that an element G is a fixpoint of T if and a post-fixpoint of T if .
- We define by transfinite induction a sequence of elements of D, where α is an ordinal, as follows:
- −
- ,
- −
- ,
- −
- for all limit ordinals β, .
- We call the least α such that the closure ordinal of T and denote it by . We call then the outcome of (iterating) T and write it alternatively as .
So an outcome is a fixpoint reached by a transfinite iteration that starts with the largest element. In general, the outcome of an operator does not need to exist but we have the following classic result due to [].3
Tarski’s Fixpoint Theorem Every monotonic operator T on has an outcome, i.e., is well-defined. Moreover,
where is the largest fixpoint of T.
In contrast, a contracting operator does not need to have a largest fixpoint. But we have the following obvious observation.
Note 1. Every contracting operator T on has an outcome,i.e., is well-defined. ☐
In Section 4 we shall need the following lemma, that modifies the corresponding lemma from [] from finite to arbitrary complete lattices.
Lemma 1. Consider two operators and on such that
- for all G, ,
- is monotonic,
- is contracting.
Proof. We first prove by transfinite induction that for all α
By the definition of the iterations we only need to consider the induction step for a successor ordinal. So suppose the claim holds for some α. Then by the first two assumptions and the induction hypothesis we have the following string of inclusions and equalities:
This shows that for all α (3) holds. By Tarski’s Fixpoint Theorem and Note 1 the outcomes of and exist, which implies the claim. ☐
2.5. Iterated Elimination of Non-Rational Strategies
In this paper we are interested in analyzing situations in which each player pursues his own notion of rationality and this information is common knowledge or true common belief. As a special case we cover then the usually analyzed situation in which all players use the same notion of rationality.
Given player i in the initial strategic game we formalize his notion of rationality using an optimality property that holds between a strategy , a set of strategies of player i and a set of joint strategies of his opponents. Intuitively, holds if is an ‘optimal’ strategy for player i within the restriction , assuming that he uses the property to select optimal strategies. In Section 4 we shall provide several natural examples of such properties.
We say that the property used by player i is monotonic if for all and
So monotonicity refers to the situation in which the set of strategies of player i is set to and the set of joint strategies of player i’s opponents is increased.
Each sequence of properties determines an operator on the restrictions of H defined by
where , , and for all
Note that in defining the set of strategies we use in the second argument of the set of player’s i strategies in the initial game H and not in the current restriction G. This captures the idea that at every stage of the elimination process player i analyzes the status of each strategy in the context of his initial set of strategies.
Since is contracting, by Note 1 it has an outcome, i.e., is well-defined. Moreover, if each is monotonic, then is monotonic and by Tarski’s Fixpoint Theorem its largest fixpoint exists and equals . Finally, G is a fixpoint of iff for all and all , holds.
Intuitively, is the result of removing from G all strategies that are not -rational. So the outcome of is the result of the iterated elimination of strategies that for player i are not -rational.
3. Two Theorems
We now assume that each player i employs some property to select his strategies, and we analyze the situation in which this information is true common belief or common knowledge. To determine which strategies are then selected by the players we shall use the operator.
We begin by fixing a belief model for the initial game H. Given an optimality property of player i we say that player i is -rational in the state ω if holds. Note that when player i believes (respectively, knows) that the state is in , the set represents his belief (respectively, his knowledge) about other players’ strategies. That is, is the restriction he believes (respectively, knows) to be relevant to his choice.
Hence captures the idea that if player i uses to select his strategy in the game he considers relevant, then in the state ω he indeed acts ‘rationally’.
To reason about common knowledge and true common belief we introduce the event
and consider the following two events constructed out of it: and . We then focus on the corresponding restrictions and .
So strategy is an element of the ith component of if for some . That is, is a strategy that player i chooses in a state in which it is common knowledge that each player j is -rational, and similarly for .
The following result then relates for arbitrary strategic games the restrictions and to the outcome of the iteration of the operator .
Theorem 1.
- (i)
- Suppose that each property is monotonic. Then for all belief models for H
- (ii)
- Suppose that each property is monotonic. Then for all knowledge models for H
- (iii)
- For some standard knowledge model for H
So part (respectively, ) states that true common belief (respectively, common knowledge) of -rationality of each player i implies that the players will choose only strategies that survive the iterated elimination of non-ϕ-rational strategies.
Proof.
Fix a belief model for H. Take a strategy that is an element of the ith component of . Thus we have for some state ω such that and . The latter implies by (1) that for some evident event F
Take now an arbitrary and . Since , it holds that player i is -rational in , i.e., holds. But F is evident, so . Moreover by (4) , so . Hence and by the monotonicity of we conclude that holds.
By the definition of this means that , i.e. is a post-fixpoint of . But is monotonic since each property is. Hence by Tarski’s Fixpoint Theorem . But and , so we conclude by the above inclusion that is an element of the ith component of . This proves the claim.
By the definition of common knowledge for all events E we have . Hence for all ϕ we have and consequently .
So part (ii) follows from part (i).
Suppose . Consider the event in the standard model for H. Then . Define each possibility correspondence by
Each is a knowledge correspondence (also when or ) and clearly F is an evident event.
Take now an arbitrary and an arbitrary state . Since is a fixpoint of and we have , so by the definition of we have . This shows that each player i is -rational in each state , i.e., .
Since F is evident, we conclude by (2) that in each state it is common knowledge that each player i is -rational, i.e., . Consequently
☐
Items and show that when each property is monotonic, for all belief models of H it holds that the joint strategies that the players choose in the states in which each player i is -rational and it is common belief that each player i is -rational (or in which it is common knowledge that each player i is -rational) are included in those that remain after the iterated elimination of the strategies that are not -rational.
Note that monotonicity of the properties was not needed to establish item .
By instantiating the ’s with specific properties we get instances of the above result that refer to specific definitions of rationality. This will allow us to relate the above result to the ones established in the literature. Before we do this we establish a result that identifies a large class of properties for which Theorem 1 does not apply.
Theorem 2. Suppose that a joint strategy exists such that
holds all . Then for some knowledge model for H the inclusion
does not hold.
Proof. We extend the standard model for H by the knowledge correspondences where for all , . Then for all ω and all
Let . Then for all , , so by the assumption each player i is -rational in , i.e., . By the definition of s the event is evident and . So by (1) . Consequently .
This yields the desired conclusion by the choice of s. ☐
4. Applications
We now analyze to what customary game-theoretic properties the above two results apply. By a belief of player i about the strategies his opponents play given the set of their joint strategies we mean one of the following possibilities:
- a joint strategy of the opponents of player i, i.e., , called a point belief,
- or, in the case the game is finite, a joint mixed strategy of the opponents of player i (i.e., , where for all ), called an independent belief,
- or, in the case the game is finite, an element of , called a correlated belief.
In the second and third case the payoff function can be lifted in the standard way to an expected payoff function , where is the corresponding set of beliefs of player i held given .
We use below the following abbreviations, where and is a set of the strategies of the opponents of player i:
- (strict dominance) for
- (weak dominance) for
In the case of finite games the relations and between a mixed strategy and a pure strategy are defined in the same way.
We now introduce natural examples of the optimality notion.
- (assuming H is finite)
- (assuming H is finite)
So and are the customary notions of strict and weak dominance and and are their counterparts for the case of dominance by a mixed strategy. Note that the notion of best response, comes in three ‘flavours’ depending on the choice of the set of beliefs.
Consider now the iterated elimination of strategies as defined in SubSection 2.5, so with the repeated reference by player i to the strategy set . For the optimality notion such a version of iterated elimination was studied in [], for it was used in [], while for it corresponds to the rationalizability notion of [].
In [], [] and [] examples are provided showing that for the properties and in general transfinite iterations (i.e., iterations beyond ) of the corresponding operator are necessary to reach the outcome. So to establish for them part of Theorem 1 transfinite iterations of the operator are necessary.
The following lemma holds.
Lemma 2. The properties and are monotonic.
Proof. Straightforward.
So Theorem 1 applies to the above three properties. In contrast, Theorem 1 does not apply to the remaining two properties and , since, as indicated in [], the corresponding operators and are not monotonic, and hence the properties and are not monotonic.
In fact, the desired inclusion does not hold and Theorem 2 applies to these two optimality properties. Indeed, consider the following game:
| L | R | |
| U | 1, 1 | 0, 1 |
| D | 1, 0 | 1, 1 |
Then the outcome of iterated elimination for both and yields . Further, we have and , and analogously for and .
So the joint strategy satisfies the conditions of Theorem 2 for both and . Note that this game also furnishes an example for non-monotonicity of since does not hold.
This shows that the optimality notions and cannot be justified in the used epistemic framework as ‘stand alone’ concepts of rationality.
5. Consequences of Common Knowledge of Rationality
In this section we show that common knowledge of rationality is sufficient to entail the customary iterated elimination of strictly dominated strategies. We also show that weak dominance is not amenable to such a treatment.
Given a sequence of properties , we introduce an operator on the restrictions of H defined by
where , , and for all
So when defining the set of strategies we use in the second argument of the set of player’s i strategies in the current restriction G. That is, determines the ‘locally’ ϕ-optimal strategies in G. In contrast, determines the ‘globally’ ϕ-optimal strategies in G, in that each player i must consider all of his strategies that occur in his strategy set in the initial game H.
So the ‘global’ form of optimality coincides with rationality, as introduced in SubSection 2.5, while the customary definition of iterated elimination of strictly (or weakly) dominated strategies refers to the iterations of the appropriate instantiation of the ‘local’ operator.
Note that the operator is non-monotonic for all non-trivial optimality notions such that for all joint strategies s, so in particular for and . Indeed, given s let denote the corresponding restriction in which each player i has a single strategy . Each restriction is a fixpoint of . By non-triviality of s we have , so for each restriction with s including an eliminated strategy the inclusion does not hold, even though . In contrast, as we saw, by virtue of Lemma 2 the operator is monotonic for and .
First we establish the following consequence of Theorem 1. When each property equals , we write here and similarly with .
Corollary 1.
- (i)
- For all belief models
- (ii)
- for all knowledge models
Proof.
By Lemma 2 and Theorem 1 Each best response to a joint strategy of the opponents is not strictly dominated, so for all restrictions G
Also, for all restrictions G, . So by Lemma 1 , which concludes the proof.
By part and the fact that . ☐
Part formalizes and justifies in the epistemic framework used here the often used statement:
- common knowledge of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies
In the case of finite games Theorem 1 implies the following result. For the case of independent beliefs it is implicitly stated in [], explicitly formulated in [] (see [, page 181]) and proved using Harsanyi type spaces in [].
Corollary 2. Assume the initial game H is finite.
- (i)
- For all belief models for H
- (ii)
- for all knowledge models for H
Proof. The argument is analogous as in the previous proof but relies on a subsidiary result and runs as follows.
Denote respectively by , and the best response property w.r.t. point, independent and correlated beliefs of the opponents. Below ϕ stands for either , or .
By Lemma 2 and Theorem 1 . Further, for all restrictions G we have both and So by Lemma 1 . But by the result of [], (page 60) (that is a modification of the original result of []), for all restrictions G we have , so , which yields the conclusion.
By and the fact that .
Finally, let us clarify the situation for the remaining two optimality notions, and . For them the inclusions of Corollaries 1 and 2 do not hold. Indeed, it suffices to consider the following initial game H:
| L | R | |
| U | 1, 0 | 1, 0 |
| D | 1, 0 | 0, 0 |
Here every strategy is a best response but D is weakly dominated by U. So both and are proper subsets of . On the other hand by Theorem 1 for some standard knowledge model for H we have . So for this knowledge model neither nor holds.
Acknowledgements
We thank one of the referees for useful comments. We acknowledge helpful discussions with Adam Brandenburger, who suggested Corollaries 1 and 2, and with Giacomo Bonanno who, together with a referee of [], suggested to incorporate common beliefs in the analysis. Joe Halpern pointed us to []. This paper was previously sent for consideration to another major game theory journal, but ultimately withdrawn because of different opinions with the referee. We would like to thank the referee and associate editor of that journal for their comments and help provided.
- 1.The concept of a monotonic property is introduced in Section 2.
- 2.Note that the notion of a belief has two meanings in the literature on epistemic analysis of strategic games, so also in this paper. From the context it is always clear which notion is used. In the modal logic terminology a belief correspondence is a frame for the modal logic KD45 and a knowledge correspondence is a frame for the modal logic S5, see, e.g. [].
- 3.We use here its ‘dual’ version in which the iterations start at the largest and not at the least element of a complete lattice.
References
- Milgrom, P.; Roberts, J. Rationalizability, learning, and equilibrium in games with strategic complementarities. Econometrica 1990, 58, 1255–1278. [Google Scholar] [CrossRef]
- Chen, Y.C.; Long, N.V.; Luo, X. Iterated strict dominance in general games. Games Econ. Behav. 2007, 61, 299–315. [Google Scholar] [CrossRef]
- Bernheim, B.D. Rationalizable strategic behavior. Econometrica 1984, 52, 1007–1028. [Google Scholar] [CrossRef]
- Brandenburger, A.; Friedenberg, A.; Keisler, H. Admissibility in games. Econometrica 2008, 76, 307–352. [Google Scholar] [CrossRef]
- Halpern, J.; Pass, R. A logical characterization of iterated admissibility. In Proceedings of the 12th Conference on Theoretical Aspects of Rationality and Knowledge (TARK XII), Stanford University, Standord, CA, USA, 6–8 July 2009; Available online: http://arxiv.org/abs/0906.4326 (accessed on 30 September 2010).
- van Benthem, J. Rational dynamics and epistemic logic in games. Int. Game Theory Rev. 2007, 9, 13–45. [Google Scholar] [CrossRef]
- Apt, K.R. The many faces of rationalizability. The B.E. J. Theoretical Econ. 2007, 7. Article 18. Available online: http://arxiv.org/abs/cs.GT/0608011 (accessed on 30th September 2010). [Google Scholar] [CrossRef]
- Apt, K.R. Relative Strength of Strategy Elimination Procedures. Econ. Bull. 2007, 3, 1–9. Available online: http://www.economicsbulletin.com/ (accessed on 30th September 2010). [Google Scholar]
- Lipman, B.L. How to decide how to decide how to …: Modeling limited rationality. Econometrica 1991, 59, 1105–1125. [Google Scholar] [CrossRef]
- Lipman, B.L. A note on the implications of common knowledge of rationality. Games Econ. Behav. 1994, 6, 114–129. [Google Scholar] [CrossRef]
- Heifetz, A.; Samet, D. Knowledge spaces with arbitrarily high rank. Games Econ. Behav. 1998, 22, 260–273. [Google Scholar] [CrossRef]
- Luo, X. General systems and ϕ-stable sets—A formal analysis of socioeconomic environments. J. Math. Econ. 2001, 36, 95–109. [Google Scholar] [CrossRef]
- Apt, K.R. Epistemic analysis of strategic games with arbitrary strategy sets. In Proceedings of the 11th Conference on Theoretical Aspects of Reasoning about Knowledge (TARK XI), Brussels, Belgium, June 25-27th, 2007; Available online: http://portal.acm.org (accessed on 30th September 2010).
- Battigalli, P.; Bonanno, G. Recent results on belief, knowledge and the epistemic foundations of game theory. Res. Econ. 1999, 53, 149–225. [Google Scholar] [CrossRef]
- Blackburn, P.; de Rijke, M.; Venema, Y. Modal Logic; Cambridge University Press: Cambridge, UK, 2001. [Google Scholar]
- Monderer, D.; Samet, D. Approximating common knowledge with common beliefs. Games Econ. Behav. 1989, 1, 170–190. [Google Scholar] [CrossRef]
- Aumann, R. Agreeing to disagree. Ann. Stat. 1976, 4, 1236–1239. [Google Scholar] [CrossRef]
- Tarski, A. A lattice-theoretic fixpoint theorem and its applications. Pacific J. Math. 1955, 5, 285–309. [Google Scholar] [CrossRef]
- Brandenburger, A.; Dekel, E. Rationalizability and correlated equilibria. Econometrica 1987, 55, 1391–1402. [Google Scholar] [CrossRef]
- Stalnaker, R. On the evaluation of solution concepts. Theor. Decis. 1994, 37, 49–73. [Google Scholar] [CrossRef]
- Brandenburger, A.; Friedenberg, A. Intrinsic correlation in games. J. Econ. Theor. 2008, 141, 28–67. [Google Scholar] [CrossRef]
- Osborne, M.J.; Rubinstein, A. A Course in Game Theory; The MIT Press: Cambridge, MA, USA, 1994. [Google Scholar]
- Pearce, D.G. Rationalizable strategic behavior and the problem of perfection. Econometrica 1984, 52, 1029–1050. [Google Scholar] [CrossRef]
© 2010 by the authors; licensee MDPI, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).