Acceptable Points in General Cooperative n-person Games

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1 20 1 Introduction In this paper, we introduce a new theory for n-person games. Like many previous theories for n-person games, it is based on the search for a reasonable steady state in the supergame, 1 i.e., the game each play of which consists of a long sequence of plays of the original game. We use two approaches: The usual approach, in which a single play is studied, and an attempt is made to find an n-tuple of strategies that intuitively speaking might be acceptable for a steady state in the supergame (Sections 4 and 5); and an approach based on a mathematical analysis of the supergame itself (Sections 6 and 7). The results we obtain by the two approaches turn out to be essentially equivalent (Sections 9 and 10). We will consider here only cooperative games, i.e., games in which coalitions are permitted; side payments will be forbidden.2 However, the ideas introduced here also apply to non-cooperative games. Subsequent papers will consider non-cooperative as well as cooperative games. We will not explicitly consider games involving chance; however, everything we say here carries over with no essential change to games involving chance. Section 2 describes the notation we will use throughout. The reader may omit this section at first and use it only for reference. Section 8 is devoted to the proof of lemmas needed in the subsequent sections; it makes strong use of the approachability-excludability theory of Blackwell [4]. Sections 11, 12, and 13 are devoted to some miscellaneous remarks and counterexamples. 2 Notation Throughout the paper, we will be concerned with an n-person game G. N will denote the set of all players; the individual players will be denoted by the positive integers 1;...; n. Ifx i is an object defined for each i A N, and if B H N, then x B will denote the set of x i where i A B; it will be called a B-vector. When B ¼ N, we will often omit the superscript and the prefix; that is, we will write x instead of x N, and will refer to x simply as a vector rather than as an N-vector. If X is a set of vectors, we denote by X B the This chapter orginally appeared in Contributions to the Theory of Games IV, Annals of Mathematics Studies 40, edited by R. D. Luce and A. W. Tucker, pp , Princeton University Press, Princeton, Reprinted with permission. 1. The name is due to Luce and Rai a [6]. 2. Of course it is known (see [1]) that the cooperative game with side payments is a special case of the cooperative game without side payments.

2 322 Strategic Games: Repeated set of all x B where x A X. When we speak of a subset B of N, i.e., of a B H N, we will mean a non-null subset, unless we specifically include the null subset. All B-vector equalities or inequalities will be taken to hold term by term. We will be concerned only with random variables taking a fixed finite number of values, and possibly with infinite sequences of such random variables. If x is a random variable ranging over a finite set Z, then the probability distribution of x may be considered as a function y from Z to the reals satisfying the relations: yðzþ X 0; z A Z ð2:1þ and X yðzþ ¼1: z A Z ð2:2þ We can then write y ¼ X z A Z yðzþz ð2:3þ where the indicates that the sum is merely symbolic and is not meant to be an ordinary sum. yðzþ is simply the probability that a random variable distributed according to y will take the value z. The set of all probability distributions on Z will be denoted by CðZÞ. The set of all pure strategies p i for player i will be denoted by P i. P is then the space of pure strategy vectors p. CðPÞ is the space of correlated strategy vectors. A correlated strategy vector is a probability distribution on the set of all pure strategy vectors, just as a mixed strategy is a probability distribution on individual strategies. In general, to make use of a correlated strategy vector, the players have to agree to consult the same random device in choosing the pure strategies they will play. Correlated strategy vectors are thus not usable in non-cooperative games. We will usually abbreviate CðPÞ to C. The prefix c- in front of a word will stand for correlated. Let X B be a space of B-vectors, and let B ¼ 6 k j¼1 B j be a partition of B into subsets. If for j ¼ 1;...; k, we have y B j A CðX B j Þ; then (y B 1 ;...; y B k ) denotes the joint probability distribution of y B 1 ;...; y B k. If Z 1 and Z 2 are finite sets and y A CðZ 1 Z 2 Þ, then yjz 1 (sometimes also written yjcðz 1 ÞÞ will be the distribution given by yjz 1 ¼ X z 1 A Z 1 z 1 X z 2 A Z 2 yðz 1 ; z 2 Þ:

3 323 If B 1 H B 2 and y B 2 A CðX B 2 Þ, then we will simply write y B 1 instead of y B 2 jx B 1. This applies to all symbols except g. Thus g B 1 is not the same as g B 2 jp B 1.(g B will be defined on C B ðpþ.) Let Z 1 and Z 2 be finite sets, and suppose we have a function f that takes Z 1 into Z 2. If nothing is said to the contrary, we will assume that the definition of f is extended linearly; that is, f is a function from CðZ 1 Þ to CðZ 2 Þ defined by f ðyþ ¼ X z 1 A Z 1 f ðz 1 Þyðz 1 Þ: If for each i A N, we have a function f i defined on X i, then we may define a vector function f on X by means of f ðxþ ¼ðf 1 ðx 1 Þ;...; f n ðx n ÞÞ ð2:4þ for all x A X. It is important to remember, though, that the inverse process does not in general work. A vector function f defined on X does not yield a unique definition of a function f i defined on X i. In general, when we have defined f i on X i, we will use the function f on X in the above sense. For p A P, the payo to the i th player will be denoted by E i ðpþ. If c A C, HðcÞ will be the mean of the distribution EðcÞ. EðcÞ is called the payo distribution when c is played, HðcÞ the expected payo when c is played. If p A P, we have HðpÞ ¼EðpÞ. The null set will be denoted by q. We will be concerned with partitions of N. Let P N denote the set of all subsets of N. Formally, a partition of N is a vector d whose components are members of P N, and which satisfies the condition j A d i () d i ¼ d j ; i; j A N: The set of all partitions of N will be denoted by D. The constant partition d N is defined by d i N ¼ N; i A N: ð2:5þ The identity partition d e is defined by d i e ¼fig; i A N: Denote by R the set of all vectors r, each of whose components r i is a member of P N containing i. Clearly D H R, and D i ¼ R i. For a given d, the number of distinct d i will be called nðd Þ. We choose a set of representatives i 1 ;...; i nðdþ, one out of each distinct d i.ifc B is a c-strategy B-vector, define

4 324 Strategic Games: Repeated eðc B Þ¼B: (The e stands for exponent; B is called the exponent of c B.) Denote by T the set of all vectors t, each of whose components is some correlated strategy B-vector (not necessarily the same B for each member of N), for which i A eðt i Þ; i A N: Let d i ðtþ ¼fjjt j ¼ t i g; i A N; t A T: ð2:6þ Then dðtþ is a partition of N, and we have d i ðtþ H eðt i Þ; i A N: Define cðtþ ¼ððt i 1 Þ di 1 ðtþ ;...; ðt i nðdðtþþ Þ di nðdðtþþ ðtþ Þ ð2:7þ where i 1 ;...; i nðdðtþþ are a set of representatives for dðtþ. In discussing games in extensive form, we will call the vertices of the game tree that are not moves by the name terminal rather than play. This is necessary to avoid confusion, as we will be dealing with repeated plays of the same game, in the more common sense of the word. As a final remark, we mention that everything we have stated probabilistically can be restated, where necessary, in the language of measure theory, and rigorously justified in that language. All sets we use can be proved to be measurable. 3 General Cooperative Games We use the word general in the title of the paper and of this section in order to emphasize that, unlike the cooperative games of von Neumann Morgenstern, the games to be considered here exclude side payments. On the other hand, full and free cooperation is permitted between the players, in the sense that they may communicate with each other freely prior to each play and form any coalitions they may consider convenient. The agreements under which the coalitions are chosen are to be considered enforceable. (However, see Section 13 for further discussion of this point.) We will usually omit the word general and refer simply to a cooperative game. This is in accordance with the usage introduced by Nash [1].

5 325 In applications, the prohibition on side payments may be the result either of a physical barrier to side payments (in economic applications this might take the form of certain provisions in an anti-trust law) or of the lack of a common unit of measurement for the payo. As has been pointed out by Rai a [8], if there is a common unit of measurement for the payo but there exists some physical barrier to the making of side payments, then the theory need only be invariant under linear transformations of the payo function that do not destroy the common unit of measurement; i.e., under transformations of the form H! ¼ ah þ b ð3:1þ where both a and b are scalar multiples of the vector (1;...; 1) (a by a positive factor, b by an arbitrary factor). If, however, there is no common unit of measurement for the payo, then the theory should be invariant under independent linear transformations of the payo function; i.e., under transformations of the form (3.1), where a is an arbitrary positive vector and b is an arbitrary vector. In fact, the theory presented in this paper is invariant under the wider class of transformations, so that the results may be used in either kind of application. Mathematically, the cooperative game is given by a vector payo function that is assumed to be linear on the space C of correlated strategy vectors. The cooperative game di ers from the non-cooperative game only in that the use of correlated strategy vectors is permitted in the former, but not in the latter. This points up a reason for studying cooperative games even if our a priori interest lies in the field of non-cooperative games only. Consider a long sequence of plays (we call this a superplay) of the game (4, 0) (0, 0) 2 (0, 0) (0, 4). One of the most natural ways for the players to proceed in such a superplay would be to alternate between playing (1, 1) and (2, 2). This would tend to happen even in the non-cooperative case, by a sort of silent gentlemen s agreement. However, the resulting payo, (2, 2), is obtainable only by a correlated strategy vector, not by mixed strategies. Thus if we wish to arrive at results that are valid for the supergame by considering a single play, we must permit ourselves the use of correlated strategy vectors. This amounts to considering cooperative games.

6 326 Strategic Games: Repeated 4 Acceptable Points Let c be a correlated strategy vector in G. Obviously, c will be a candidate for a possible steady state in the supergame unless some subset B of the players can, by concerted action, increase their payo. Here it is not su cient that the players of B be able to increase their payo s by changing their strategies while the players of N B maintain their strategies as they are. For the players of N B will not in general maintain their strategies fixed in the face of a change on the part of B, but will also change their strategies in order to meet the new conditions; thus B s glory would be short-lived indeed. In order to rule out c as a candidate for a possible steady state, we have to be sure that the players of N B cannot prevent the players of B from improving their payo by concerted action. Of course, we must require that all the members of B obtain more at the new point than they do at c, for they must all have an incentive to cooperate in the venture. definition 4.1 Let c 0 A C. c 0 is said to be c-acceptable if there is no B H N such that for each c N B A C N B, there is a c B A C B for which H B ðc B ; c N B Þ > H B ðc 0 Þ: We write c-acceptable instead of acceptable because in subsequent papers of this series, we will be defining a slightly di erent kind of acceptability, and we will use prefixes to distinguish them. When in heuristic discussion in the sequel we use the word acceptable without a prefix, then it is to be taken to mean acceptable with an arbitrary prefix (but one that is fixed throughout the discussion). For the purposes of this paper alone, acceptable can be taken to mean the same thing as c-acceptable. The set of all c-acceptable c-strategy vectors is denoted by A c.note that the notion of acceptability is a global one. In other words, whether or not a point is acceptable depends only on the payo at that point, not on the point itself. This is also easy to accept from the intuitive standpoint; as long as he is getting the same payo, it makes little di erence to a player which strategy he is playing. definition 4.2 c A A c, we have A payo vector h is said to be c-acceptable, if for some HðcÞ ¼h: It will be convenient in the sequel to have available the following trivial restatement of 4.2.

7 327 lemma 4.3 A payo vector h is c-acceptable if and only if for each B H N, there is a c N B A C N B, such that for all c B A C B, there is an i A B for which H i ðc B ; c N B Þ X h i : 5 Two-Person, Zero-Sum Games A sine qua non of theories of n-person games is that for two-person, zerosum games, they reduce to the von Neumann theory. Because of the global nature of our theory, we can only expect that every acceptable payo vector yield to each player the value of the game to that player. This is indeed the case. theorem 1 In a two-person, zero-sum game G, a payo vector h is c- acceptable if and only if h 1 ¼ v; ð5:1þ where v is the value of G to player 1. Proof Let h be c-acceptable. From Lemma 4.3 applied to B ¼f1g, we deduce that there is a c 2 0 A C2, such that for all c 1 A C 1, we have H 1 ðc 1 ; c 2 0 Þ W h1 : Hence max H 1 ðc 1 ; c 2 c 1 A C 1 0 Þ W h1 : Hence min c 2 A C 2 max H 1 ðc 1 ; c 2 Þ W h 1 : ð5:2þ c 1 A C 1 C 1 and C 2 are the mixed strategy spaces for players 1 and 2 respectively. Hence the left side of (5.2) is v, and we deduce v W h 1 : ð5:3þ The value of G to player 2 is v. Proceeding as in the proof of (5.3), we obtain v W h 2 : ð5:4þ But h 2 ¼ h 1 : ð5:5þ

8 328 Strategic Games: Repeated Combining (5.4) and (5.5), we obtain v X h 1 : ð5:6þ Combining (5.3) and (5.6), we obtain (5.1). Conversely, assume (5.1). Then (5.3) and (5.2) follow at once. But for B ¼f1g, (5.2) is precisely the condition for c-acceptability given by Lemma 4.3. Similarly we establish the condition for B ¼f2g. To establish it for B ¼f1, 2g, note that for any (c 1, c 2 ), we have H 1 ðc 1 ; c 2 ÞþH 2 ðc 1 ; c 2 Þ¼0 ¼ h 1 þ h 2 ; whence we must have either H 1 ðc 1 ; c 2 Þ W h 1 or H 2 ðc 1 ; c 2 Þ W h 2 : Thus h is c-acceptable. 6 Strategies and Payo s in the Supergame In the notion of supergame that will be used in this paper, each superplay consists of an infinite number of plays of the original game G. On the face of it, this would seem to be unrealistic, but actually it is more realistic than the notion in which each superplay consists of a fixed finite (large) number of plays of G. In the latter notion, the fact that the players know when they have arrived at the last play becomes the decisive factor in the analysis, overshadowing all other considerations.3 This is unnatural, because in the usual case, the players can always anticipate that there will still take place in the future an indefinite number of plays. This is especially true in political and economic applications, and even holds true for the neighborhood poker club. Of course when looked at in the large, nobody really expects an infinite number of plays to take place; on the other hand, after each play we do expect that there will be more. A. W. Tucker has pointed out that this condition is mathematically equivalent to an infinite sequence of plays, so that is what our notion of supergame will consist of. Roughly speaking, we will be interested in behavior strategies in the supergame; that is, we will be interested in strategy vectors that determine 3. See, for example, the excellent analysis of the supergame of the game known as the Prisoner s Dilemma that appears in 5.5 of [6].

9 329 the c-strategy vector to be played on each play as a function of the information possessed by the players about the outcomes of the previous plays. Before we pass to the formal definition of a supergame c-strategy vector, let us examine in detail the procedure followed during the play of a cooperative supergame. The first question to be answered is: What information about the outcome of each previous play does each player i actually possess? The most he can know is exactly what pure strategy vector was actually played; the least he can be sure of knowing, in every game, is the strategy he himself played and the payo he himself received. In between is a whole range of possibilities, depending on the rules of G. The situation can be concisely described by means of a function u i that takes P onto some identification space of P. We define u i so that for p 1, p 2 A P, u i ðp 1 Þ¼u i ðp 2 Þ if and only if player i cannot tell after a play of G, whether the vector p 1 or the vector p 2 has been played. The minimum knowledge that each player i has, in accordance with our remarks above, insures us that if u i ðp 1 Þ¼u i ðp 2 Þ; then p i 1 ¼ pi 2 and H i ðp 1 Þ¼H i ðp 2 Þ: Every game G has associated with it an information vector u satisfying these conditions. In particular, these conditions assure us of the existence of functions f i and c i which map u i ðpþ onto P i and H i ðpþ respectively. Some relations connecting the vector functions H, f, c, and u are the following: f u ¼ identity c u ¼ H c ¼ H f: The information vector just defined is not included in the classical formulation of the extensive form of a game, as given, say, in [3]. That is because the state of information at the end of a game has heretofore been of little interest, as the payo in no way depends on it. In a number of consecutive plays of a game, however, it is seen to be of vital importance. Incidentally, inclusion of this concept in the extensive structure of a game necessitates a revision in the notion of equivalence as formulated in [5].

10 330 Strategic Games: Repeated We hope to treat the subject in more detail in a subsequent paper. For the present, we content ourselves with the remark that the information vector may be included in the extensive description of the game by associating with each player i, an information partition on the set of all terminals. In a game of perfect information, this partition would be the identity partition for each i. All that we have said in this section up to now is quite general, applying to the non-cooperative as well as to the cooperative case. In the latter case, the information function does not exhaust the information that a player has to work with. Prior to each play, consultation takes place among the various players to determine the constitution of the coalitions and the correlated strategy B-vector that each coalition B will use. Formally, each player designates the coalition B to which he wishes to belong, and the correlated strategy B-vector he wishes B to play. Those players who can agree among each other form coalitions and play the agreed upon c-strategy B-vector.4 Naturally, although each player knows nothing about the coalitions in which the other players participate, he does remember the coalition B of which he himself was a member on previous plays. The formal definition is as follows: definition 6.1 A supergame c-strategy f i for player i is an infinite sequence of functions f0 i ; f 1 i ;...; f k i ;... where fk i is a function from ððu1 i Ri 1 ÞðU k i Ri k ÞÞ to T i ; here Uj i is a copy of u i ðpþ and Rj i is a copy of R i,forj ¼ 1;...; k. The vector f is called a supergame c-strategy vector. In the sequel, we will denote Uj i Rj i by Jj i. J j i represents the information about the j th play available to player i. To define the payo to a supergame c-strategy vector, we must first define the payo to a given superplay, as a function of its individual constituent plays. For this purpose, we use the arithmetic mean of the payo s (in the limiting case, this amounts to the first Cesàro sum); Blackwell [4] also used the arithmetic mean under similar circumstances. Heuristically, one can argue both for and against this method; in my mind the heuristic advantages outweigh the disadvantages. Other methods have been proposed (see [6]) for obtaining the superplay payo from the pay- 4. If B 1 H B 2 and every member of B 1 proposed (B 2, c B2 ) while the members of B 2 B 1 proposed something else, then the members of B 1 form a coalition and play c B1.

11 331 o s to its constituent plays; the most prominent seems to be the discounting of future payo s back to the present, using a fixed rate of interest. This has the disadvantage of putting an unnaturally heavy stress on the beginning of the supergame. Nevertheless, it would be interesting to see an analysis based on this payo notion, especially for certain kinds of economic applications. A more perplexing problem in defining the payo to a supergame c-strategy vector f is that of somehow combining the various possible superplays that might occur if f is played. The first impulse is to use some notion of expected payo. We shall indeed define such a notion, but it is not an appropriate criterion for the players in choosing their supergame c-strategy. The chief reason for our being interested in expected payo s for individual plays is that in a long sequence of plays, the law of large numbers turns an expected payo into an actual payo. A payo for the whole superplay that is only expected, but not eventually approached, will not satisfy most players. Thus if a player has joined a coalition on the strength of a high expectation and is being disappointed in this expectation, he will soon express his disappointment by resigning from the coalition, regardless of his originally high expectation. For a clear example of the pitfalls of expected payo s, see Section 12. What is required is some kind of criterion based on a law of large numbers. We give a restricted definition of this kind in this section, but reasoning of this type in general will dominate the remainder of the paper. Let us first return to the question of expected payo. For each t A T, define sðtþ ¼ðuðcðtÞÞ; dðtþþ: ð6:2þ Let f be a supergame c-strategy vector. For each k X 1, we may define a member z k ð f Þ¼z k of CðJ 1... J k Þ recursively as follows: z 1 ¼ sð f 0 Þ ð6:3þ X z k ¼ z k 1 ðyþðy; sð f k 1 ðyþþþ; k > 1: ð6:4þ y A J 1 J k 1 z k is the probability distribution of possible outcomes of plays up to the k th. Define a member x k ð f Þ¼x k of CðJ k Þ as follows: x k ¼ sð f k 1 ðz k 1 ÞÞ; k X 1: ð6:5þ x k is the probability distribution of outcomes of the k th play. Finally, define E k ¼ E k ð f Þ and H k ¼ H k ð f Þ by E k ¼ Eðcð f k 1 ðz k 1 ÞÞÞ ð6:6þ

12 332 Strategic Games: Repeated and H k ¼ Hðcð f k 1 ðz k 1 ÞÞÞ: ð6:7þ E k represents the probability distribution of possible payo vectors on the k th play; H k is the expected payo for the k th play. If 1 X k Hð f Þ¼ lim H r ð f Þ k r¼1 ð6:8þ exists, then f is said to be summable in the mean. Let v ¼ðv 1 ;...; v k ;...Þ be a sequence of random variables in which v k is distributed according to the distribution x k ð f Þ. These random variables are not in general independent. Instead of saying that the random variables v k are distributed according to x k ð f Þ, we will sometimes say that the random variable v is distributed according to f. The probability of a statement concerning a random variable v distributed according to f will usually be denoted Prob f. definition 6.9 A supergame c-strategy vector f is said to be summable if it is summable in the mean and if a sequence of random variables distributed according to E k ð f Þ obeys the strong law of large numbers.5 If v is an infinite sequence ðv 1 ;...; v k ;...Þ where v k A J k for all k, define H k ðvþ ¼cðv k ju k Þð¼ Hðfðv k ju k ÞÞÞ ð6:10þ and S k ðvþ ¼ 1 k X k j¼1 H j ðvþ: ð6:11þ Note that if v is a random variable distributed according to f, then H k ðvþ is a random variable distributed according to E k ð f Þ. lemma 6.12 A necessary and su cient condition that a supergame c- strategy vector f be summable is that there exist a vector Hð f Þ such that for each vector e > 0, we have lim Prob f ðjs r ðvþ Hð f Þj X e for some r X kþ ¼0: Furthermore, this Hð f Þ is then identical with the Hð f Þ defined by (6.8). The proof, which is straightforward, will be omitted. 5. See [2], p The law is there stated for one dimensional random variables; the extension to n dimensions is straightforward.

13 333 7 Strong Equilibrium Points When we come to investigate what supergame c-strategy vectors f are liable actually to occur, we are faced with a problem somewhat di erent from the one we discussed in Section 4. There one could always look forward to future plays in order to punish deviations by the other players. In the supergame, however, there is only one superplay. Thus the players will have to make sure the first time that deviations won t pay. This amounts to saying that no coalition B can increase the payo of all its members by substituting a di erent supergame c-strategy B-vector g B while N B maintains the supergame c-strategy ðn BÞ-vector f N B.It is clear that such an f would be very strongly stable, since no coalition could have any incentive to move away from it, especially if we demand that B cannot even increase its payo with positive probability, no matter how small. This is a much stronger version of what corresponds in the supergame to an ordinary equilibrium point. The formal definition is as follows: definition Let f be a summable supergame c-strategy vector. f is a strong equilibrium c-point if there is no B H N for which there is a supergame c-strategy vector g satisfying g N B ¼ f N B ð7:1þ and lim Prob gðsr B ðvþ X HB ð f Þþe B for some r X kþ > 0 for some B-vector e B > 0: ð7:2þ (The limit exists because the sequence involved is monotone decreasing.) The set of all strong equilibrium c-points is denoted by S c. It is necessary to use the form Sr BðvÞ X HB ð f Þþe B rather than Sr BðvÞ > HB ð f Þ because substitution of the latter statement would make condition 7.2 true even for f ¼ g. We wish to include only those cases in which substitution of g for f will yield B an advantage that at least does not tend to the vanishing point, doubtful and rare as it may be. Condition 7.2 is very weak, which means that the concept of strong equilibrium c-point is a very strong one (i.e., comparatively few supergame c-strategy vectors are strong equilibrium c-points). On the other end of the spectrum, we could replace 7.2 by

14 334 Strategic Games: Repeated lim Prob gðsr B ðvþ X HB ð f Þþe B for all r X kþ ¼1 for some B-vector e B > 0: ð7:3þ Denote by ~ S c the set of supergame c-strategy vectors obtained when 7.3 is substituted for 7.2 in the definition of strong equilibrium c-point. It is easy to see that 7:3 ¼)7:2; whence it follows that S c H ~ S c and HðS c Þ H Hð ~ S c Þ: ð7:4þ We will demonstrate the opposite inequality as well. This shows that the notion of strong equilibrium point does not really depend on the strength of the condition Application of Approachability and Excludability Theory For two-person, zero-sum games with vector payo s, Blackwell [4] has defined the notion of approachability or excludability of a set in the payo space with a supergame strategy employed by one or the other of the players. Blackwell does not use the information vector u which we introduced in Section 6, but apart from that, our Definition 6.1 applied to two-person, zero-sum games reduces to his definition of supergame strategy (for games not involving chance). Most of his definitions and results can be used here without any changes being necessary due to our use of the information vector. Let us consider the two-person, zero-sum game with vector payo s that is obtained from our game G by considering the coalition B to be the first player and the coalition N B the second player, the payo to the first player being given by H B. lemma 8.1 Let Lð f ; e B Þ denote the closed convex set consisting of all B-vectors l B for which l B X H B ð f Þþe B : Then if there is an e B > 0 such that Lð f ; e B Þ is approachable with g B, then 7.3 holds. Proof This lemma follows at once from the definition of approachability; see Section 1 of [4]. Our games do not involve chance, so the elements of the game matrix should be considered as B-vectors rather than probability distributions on B-vectors. We have abbreviated

15 335 approachable in the game matrix to approachable ; this will be done throughout the sequel. lemma 8.2 If there is an e B > 0 such that, for each c N B A C N B, there is a c B A C B for which H B ðc B ; c N B Þ X H B ð f Þþe B ; then there is a g B for which 7.3 holds. Proof The condition given in the lemma is equivalent to the statement that for each c N B A C N B, H B ðc B ; c N B Þ intersects Lð f ; e B Þ. In accordance with Theorem 3 of [4], this in turn is equivalent to the statement that there is a g B with which Lð f ; e B Þ is approachable. Applying 8.1, we obtain the conclusion. The information situation in [4] is slightly di erent from ours. In our application, the requirements of [4] may be stated as follows: Both B and N B know the payo s to B on each previous play; nothing else is known. In our situation, B knows its own previous payo s, but N B need not know what the payo s to B were; on the other hand, both B and N B may have information given by the information function, that they do not have in [4]. An analysis of the proof of Theorem 3 of [4] shows that these di erences do not a ect the truth of the theorem, so that we may still apply it here. To see this intuitively, note that the only di erence that could interfere with the approachability of Lð f ; e B Þ with g B would be the additional information that N B has in our case that it does not have in [4]. Examination of the proof of Theorem 3 of [4] indicates that g B k depends only on the previous payo s, and can be defined for any set of previous payo s without a ecting the truth of the theorem; thus no amount of additional information can possibly help N B in preventing B from approaching Lð f ; e B Þ with g B. lemma 8.3 If there is a c N B A C N B (called g N B ) such that for each c B A C B, there is an i A B for which H i ðc B ; g N B Þ W H i ð f Þ; then for every B-vector e B > 0, and every supergame c-strategy vector b for which for all ðv 1 ;...; v k Þ, we have b i k ðv 1;...; v k Þ¼g N B ; i A N B; k X 0; ð8:4þ we have lim Prob bðsr B ðvþ X HB ð f Þþe B for some r X kþ ¼0:

16 336 Strategic Games: Repeated Proof The hypothesis of the lemma is equivalent to the assertion that for each e B > 0, Lð f ; e B Þ fails to intersect HðC B ; g N B Þ. Applying Theorem 3 of [4], we conclude that for each e B > 0, Lð f ; e B Þ is excludable with the supergame c-strategy ðn BÞ-vector given by (8.4). From the definition of excludability (Section 1 of [4]) it then follows that there is a number d > 0 such that lim Prob b (For all r X k, there is an i A B such that S i r ðvþ < H i ð f Þþe i dþ ¼1; whence lim Prob bðs B r ðvþ X HB ð f Þþe B for some r X kþ ¼0: 9 The Main Theorem: First Half We will now show that our two approaches culminating in the definition of c-acceptability (4.1) and strong equilibrium (7.1, 7.2, and 7.3) actually yield results that are essentially the same. More precisely, for every c-acceptable strategy vector c, there is a strong equilibrium c-point (according to either 7.2 or 7.3) in supergame c-strategies that has the same payo as c; and conversely. Thus c-acceptable points for a single play are seen to correspond exactly to strong equilibrium c-points in the supergame. The main theorem can be concisely stated by means of the equation HðA c Þ¼HðS c Þð¼ Hð ~ S c ÞÞ: This section is devoted to the proof of the relation Hð ~ S c Þ H HðA c Þ: The proof rests heavily on Lemma 8.2. In addition to 8.2, the main fact needed is that if B cannot be prevented from obtaining more than h B, then they cannot be prevented from obtaining a fixed amount more than h B either. This is shown in Lemma 9.1. lemma 9.1 Let h be a vector and B be a subset of N. If for each c N B A C N B, there is a c B A C B for which H B ðc B ; c N B Þ > h B ; then there is a positive B-vector e B such that for each c N B A C N B, there is a c B A C B for which

17 337 H B ðc B ; c N B Þ X h B þ e B : Proof We first remark that if Gðx; yþ is a continuous real-valued function of two variables x and y ranging over compact sets X and Y respectively, then the function defined by FðyÞ ¼max Gðx; yþ x A X is continuous on Y. Now define a function F on C N B by Fðc N B Þ¼ max c B A C B min ðh i ðc B ; c N B Þ h i Þ: i A B By the above remark, F is continuous. Since C N B is compact, F takes on its minimum at a point c N B 0 in C N B. By the hypothesis of the lemma, Fðc N B 0 Þ > 0: Setting e i ¼ Fðc N B 0 Þ for all i A B, we obtain the conclusion of the lemma. theorem 2 Hð ~ S c Þ H HðA c Þ. Proof Let f be a summable supergame c-strategy vector; set h ¼ Hð f Þ: Suppose h B HðA c Þ; ð9:2þ i.e., suppose there is a B for which the hypothesis of Lemma 9.1 holds. Then the conclusion of Lemma 9.1, which is the same as the hypothesis of Lemma 8.2, holds. Hence we deduce the conclusion of Lemma 8.2, i.e., there is a g B for which 7.3 holds. Setting g N B ¼ f N B ; we obtain a B and a g obeying 7.1 and 7.3, whence f B ~ S c : ð9:3þ As we can go through the same argument for any f satisfying h ¼ Hð f Þ, we may deduce from (9.3) that h B Hð ~ S c Þ: ð9:4þ

18 338 Strategic Games: Repeated We have shown that (9.2) ¼) (9.4), whence we can deduce that Hð ~ S c Þ H HðA c Þ; which is what we set out to prove. 10 The Main Theorem: Second Half This section is devoted to the proof of the relation HðA c Þ H HðS c Þ; together with Theorem 2, this yields the main theorem. The train of thought of the proof is somewhat as follows: Suppose h to be a c-acceptable payo. It is easy to set up a supergame c-strategy vector f whose payo is h. But we must also incorporate in f a foolproof system for the punishment of any deviators; f must make sure that crime does not pay. The machinery for accomplishing this is at hand; by the definition of c-acceptability, for each B there is a c-strategy (N B)-vector g N B whose use prevents B from obtaining more than h B. It remains only to find the culprits. To do this, we note that any players who at one time or another deviated from f were at the time of their deviation certainly not included in the same coalition as the orthodox players. Since each player knows who was in his coalition on all previous plays, the deviators are thus easily spotted. The set B k of players who deviated on some play up to the (k þ 1) st is monotone increasing with k. Every time it grows, i.e., every time another player joins the ranks of the deviators, the remaining players revise their strategy to punish at least one of the new set of deviators. Since N is finite, there must be a set B that includes all the deviators and that is actually attained by B k after a finite number of plays. The use of the strategy g N B will then make certain that crime does not pay for at least one of the deviators. The proof is complicated by the fact that B k and B usually depend on which pure strategies were chosen from among those considered by the correlated strategy vectors used on previous plays. The strong equilibrium point f just described is one of unrelenting ferocity 6 against o enders. It exhibits a zeal for meting out justice that is entirely oblivious to the sometimes dire consequences to oneself or to the other faithful i.e., those who have not deviated. There are other, more reasonable strong equilibrium points, which give deviating players a chance to return to the fold. These are important in connection with the general non-cooperative game; I will return to them in a subsequent 6. The term is due to Luce and Rai a [6].

19 339 paper on that topic. Here it is simpler and just as e cacious to use the strong equilibrium point of unrelenting ferocity. theorem 3 HðA c Þ H HðS c Þ. Proof Let h A HðA c Þ, and suppose g N A A c is such that Hðg N Þ¼h: ð10:1þ Then by 4.3, for each B H N there is a c N B A C N B, which we will call g N B, such that for each c B A C B, there is an i A B for which H i ðc B ; g N B Þ W h i : ð10:2þ Now define a supergame c-strategy vector f as follows: fo i ¼ gn ; i A N fk iðvi 1 ;...; vi k Þ¼gvi k jri ; k > 0; i A N; vj i A Jj i; j W k: ð10:3þ We must prove that the payo to f is h and that f is a strong equilibrium c-point. It is convenient to break the proof into a number of lemmas. However, these lemmas will depend on previous assumptions and formulae, and are valid only within the context of this proof. They will be numbered like ordinary formulae used within the proof. lemma 10.4 For k > 0 and i A N, we have fk i ðz kþ¼g N : Proof The proof is by induction on k. For k ¼ 0, (10.4) follows at once from (10.3). Assume (10.4) for a given k. Applying (2.6) and (2.7), we obtain cð f k ðz k ÞÞ ¼ g N and dð f k ðz k ÞÞ ¼ d N : Hence, by (6.2), sð f k ðz k ÞÞ ¼ ðuðg N Þ; d N Þ: ð10:5þ Now by (6.4) and the linearity of fk i we have f i kþ1 ðz kþ1þ ¼ ¼ X y A J 1...J k z k ðyþ f i kþ1 ðy; sð f kðz k ÞÞÞ X y A J 1...J k z k ðyþ f i kþ1 ðy; ðuðgn Þ; d N ÞÞ ðby ð10:5þþ

20 340 Strategic Games: Repeated ¼ X y A J 1...J k z k ðyþ f i kþ1 ðyi ; ðu i ðg N Þ; NÞÞ X ¼ z k ðyþg N y A J 1...J k X ¼ g N z k ðyþ y A J 1...J k ¼ g N : ðby ð2:4þ and ð2:5þþ ðby ð10:3þþ ðby ð2:2þþ This completes the induction and the proof of the lemma. lemma 10.6 of cð f j ðz j ÞÞ. For k, j X 0 and k 0 j, cð f k ðz k ÞÞ is statistically independent Proof By (10.3), the choice of strategies after each play depends only on the coalitions previously chosen. Thus the sequence of partitions of N into coalitions is strictly determined. For a given play, the choice of c- strategy B-vectors depends only on this sequence (which is, in fact, a sequence of constant partitions), and not on the strategies previously chosen. This completes the proof. lemma 10.7 f is summable, and Hð f Þ¼h. Proof Applying (2.7) to (10.4), we obtain cð f k ðz k ÞÞ ¼ g N ; whence by (6.6) E k ¼ Eðcð f k ðz k ÞÞÞ ¼ Eðg N Þ: ð10:8þ By Lemma 10.6, the strong law of large numbers 7 applies to each component of cð f k ðz k ÞÞ, hence to cð f k ðz k ÞÞ itself, and hence also to E k.by (10.8) and (6.7), we have H k ¼ Hðg N Þ ¼ h: ðby ð10:1þþ Hence 1 X k Hð f Þ¼ lim H r k r¼1 1 ¼ lim k kh ðby ð6:8þþ 7. See [2], p. 207, The Kolmogoro Criterion, or p. 208, the Theorem.

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