PERMANENTLY OPTIMAL STRATEGIES IN EXTENSIVE GAMES

Similar documents
SF2972: Game theory. Mark Voorneveld, February 2, 2015

Game theory attempts to mathematically. capture behavior in strategic situations, or. games, in which an individual s success in

Math 152: Applicable Mathematics and Computing

2. Extensive Form Games

Computational aspects of two-player zero-sum games Course notes for Computational Game Theory Section 3 Fall 2010

Contents. MA 327/ECO 327 Introduction to Game Theory Fall 2017 Notes. 1 Wednesday, August Friday, August Monday, August 28 6

2. The Extensive Form of a Game

Behavioral Strategies in Zero-Sum Games in Extensive Form

The tenure game. The tenure game. Winning strategies for the tenure game. Winning condition for the tenure game

ON MULTIPLICATIVE SEMIGROUPS OF RESIDUE CLASSES

Computing Nash Equilibrium; Maxmin

Opponent Models and Knowledge Symmetry in Game-Tree Search

Mixed Strategies; Maxmin

Game Theory Refresher. Muriel Niederle. February 3, A set of players (here for simplicity only 2 players, all generalized to N players).

What is counting? (how many ways of doing things) how many possible ways to choose 4 people from 10?


Odd king tours on even chessboards

Game Theory Lecturer: Ji Liu Thanks for Jerry Zhu's slides

Topic 1: defining games and strategies. SF2972: Game theory. Not allowed: Extensive form game: formal definition

Game Theory: The Basics. Theory of Games and Economics Behavior John Von Neumann and Oskar Morgenstern (1943)

A SET OF POSTULATES FOR GENERAL PROJECTIVE GEOMETRY*

Circular Nim Games. S. Heubach 1 M. Dufour 2. May 7, 2010 Math Colloquium, Cal Poly San Luis Obispo

Extensive-Form Correlated Equilibrium: Definition and Computational Complexity

Advanced Microeconomics: Game Theory

Belief-based rational decisions. Sergei Artemov

Extensive Form Games. Mihai Manea MIT

GEOGRAPHY PLAYED ON AN N-CYCLE TIMES A 4-CYCLE

Minmax and Dominance

Dynamic Games: Backward Induction and Subgame Perfection

Overview GAME THEORY. Basic notions

Graph Nim. PURE Insights. Breeann Flesch Western Oregon University,

Distributed Optimization and Games

Chapter 2. Permutations and Combinations

28,800 Extremely Magic 5 5 Squares Arthur Holshouser. Harold Reiter.

Notes for Recitation 3

Design of intelligent surveillance systems: a game theoretic case. Nicola Basilico Department of Computer Science University of Milan

Advanced Microeconomics (Economics 104) Spring 2011 Strategic games I

Extensive Games with Perfect Information A Mini Tutorial

GOLDEN AND SILVER RATIOS IN BARGAINING

Lecture 6: Basics of Game Theory

Summary Overview of Topics in Econ 30200b: Decision theory: strong and weak domination by randomized strategies, domination theorem, expected utility

Self-interested agents What is Game Theory? Example Matrix Games. Game Theory Intro. Lecture 3. Game Theory Intro Lecture 3, Slide 1

Distribution of Aces Among Dealt Hands

Simple Decision Heuristics in Perfec Games. The original publication is availabl. Press

On the Periodicity of Graph Games

Game Theory and Economics of Contracts Lecture 4 Basics in Game Theory (2)

Pattern Avoidance in Unimodal and V-unimodal Permutations

Edge-disjoint tree representation of three tree degree sequences

17. Symmetries. Thus, the example above corresponds to the matrix: We shall now look at how permutations relate to trees.

A Note on Downup Permutations and Increasing Trees DAVID CALLAN. Department of Statistics. Medical Science Center University Ave

Distributed Optimization and Games

and problem sheet 7

Two-person symmetric whist

CHAPTER LEARNING OUTCOMES. By the end of this section, students will be able to:

RMT 2015 Power Round Solutions February 14, 2015

MA 524 Midterm Solutions October 16, 2018

Resource Allocation and Decision Analysis (ECON 8010) Spring 2014 Foundations of Game Theory

CSE 20 DISCRETE MATH. Fall

SOME MORE DECREASE AND CONQUER ALGORITHMS

Math 3338: Probability (Fall 2006)

Extensive Games with Perfect Information. Start by restricting attention to games without simultaneous moves and without nature (no randomness).

Best Response to Tight and Loose Opponents in the Borel and von Neumann Poker Models

A variation on the game SET

Concatenated group theoretic codes for binary asymmetric channels*

ECON 282 Final Practice Problems

Sequential games. Moty Katzman. November 14, 2017

SOLUTIONS FOR PROBLEM SET 4

X = {1, 2,...,n} n 1f 2f 3f... nf

2. Basics of Noncooperative Games

THE ASSOCIATION OF MATHEMATICS TEACHERS OF NEW JERSEY 2018 ANNUAL WINTER CONFERENCE FOSTERING GROWTH MINDSETS IN EVERY MATH CLASSROOM

Axiom A-1: To every angle there corresponds a unique, real number, 0 < < 180.

Introduction to probability

A tournament problem

THE NATURE OF RETROGRADE ANALYSIS FOR CHINESE CHESS 1

Math 464: Linear Optimization and Game

Online Computation and Competitive Analysis

Formidable Fourteen Puzzle = 6. Boxing Match Example. Part II - Sums of Games. Sums of Games. Example Contd. Mathematical Games II Sums of Games

Game Theory and Algorithms Lecture 19: Nim & Impartial Combinatorial Games

SYMMETRIES OF FIBONACCI POINTS, MOD m

Dominant and Dominated Strategies

Tiling Problems. This document supersedes the earlier notes posted about the tiling problem. 1 An Undecidable Problem about Tilings of the Plane

Topics to be covered

VARIATIONS ON NARROW DOTS-AND-BOXES AND DOTS-AND-TRIANGLES

WHEN PRISONERS ENTER BATTLE: NATURAL CONNECTIONS IN 2 X 2 SYMMETRIC GAMES. by: Sarah Heilig

ZERO-SUM GAMES WITH "6ALMOST" PERFECT INFORMATION*

Game Theory. Department of Electronics EL-766 Spring Hasan Mahmood

Repeated Games. Economics Microeconomic Theory II: Strategic Behavior. Shih En Lu. Simon Fraser University (with thanks to Anke Kessler)

Surreal Numbers and Games. February 2010

Crossing Game Strategies

3 Game Theory II: Sequential-Move and Repeated Games

The simplest games (from the perspective of logical structure) are those in which agents have perfect information, meaning that at every point where e

Introduction to Algorithms / Algorithms I Lecturer: Michael Dinitz Topic: Algorithms and Game Theory Date: 12/4/14

Multiple Agents. Why can t we all just get along? (Rodney King)

CSCI 699: Topics in Learning and Game Theory Fall 2017 Lecture 3: Intro to Game Theory. Instructor: Shaddin Dughmi

Math 127: Equivalence Relations

(b) In the position given in the figure below, find a winning move, if any. (b) In the position given in Figure 4.2, find a winning move, if any.

The Chinese Remainder Theorem

Generating trees and pattern avoidance in alternating permutations

Commuting Graphs on Dihedral Group

Colouring tiles. Paul Hunter. June 2010

Transcription:

PERMANENTLY OPTIMAL STRATEGIES IN EXTENSIVE GAMES W. H. CLINGMAN I. Introduction. The objective of this study is to develop a relationship between the information pattern in extensive games and the existence of permanently optimal strategies. The investigation has been restricted to zero-sum, two-person games, and the notation of Kuhn [l] is used throughout. Morgenstern and Von Neumann [2] have demonstrated that in a two-person, zero-sum game with perfect information, each player has pure strategies which are optimal strategies. In other words, if 3C2(ri, t2) is the payment made to player 2 when players 1 and 2 choose strategies n and r2 respectively, there exist a fi, t2, and v0 such that 3C2(i"i, f2) ^ Vo for all n, 3C2(ti, t2) ^ Vo for all t,. The strategy f2 insures player 2 that his gain will be at least Vo, independent of the strategy chosen by player 1. Likewise, the strategy fi insures player 1 that his loss will be no more than vn, independent of the strategy chosen by player 2. Von Neumann and Morgenstern [2] also state the theorem that if both players have perfect information they have pure strategies, t* and r*, which are permanently optimal. 3C2(ti, t2*) = max,, 3C2(n, t2) for all n; 3C2(ti*, t2) = minri 3C2(ti, t2) for all t2. The pure strategy t* insures player 2 of maximizing his gain independent of the choice of player 1. It follows that a permanently optimal strategy is also an optimal strategy. The converse is not true, since an optimal strategy for player 2 may not take advantage of a mistake by player 1 (i.e., player 1 not choosing an optimal strategy). Dalkey [3] has generalized the conditions for the existence of pure, optimal strategies in terms of the information pattern of the game. He has established a necessary and sufficient condition that a twoperson game have pure, optimal strategies independent of the particular pay-oft function or the probability distribution assigned to chance moves. This condition is that at any move a player knows all Received by the editors January 27, 1965. 156

PERMANENTLY OPTIMAL STRATEGIES IN EXTENSIVE GAMES 157 preceding moves of his opponents and knows at least as much as his opponents knew when they made those moves. In this paper the conditions are generalized for the existence of permanently optimal strategies in two-person games. It will be shown that a sufficient condition for a player to have a permanently optimal strategy (either pure or mixed) in a game T is that the information withheld from the player in V is inessential. That is, if the player is given this information, he will not have any new strategy which will give him a greater gain than in the original game. It will also be shown that a necessary condition for a player to have a permanently optimal strategy in a game with no chance moves is that the information withheld from the player is inessential. These results involve the payoffs and chance probabilities as well as the informational structure of the game. II. Notations. Following the notation of Kuhn, the extensive form of a game is described as follows: A game T is a game tree K with the following specifications: 1. The game tree K is a finite tree with a distinguished vertex 0 which is embedded in an oriented plane. The alternatives at a vertex xek are the edges incident at x and lying in components of K which do not contain O if we cut K at x. Those vertices with alternatives are moves and those without alternatives are plays. The alternatives at each move are numbered. A, is defined as the set of all moves with j alternatives. 2. There is a player partition of the moves into sets 730, Bi, B2. The moves in 730 are called chance moves. The moves in 73, are called personal moves of player i. 3. There is a partition of the moves into information sets U such that each U is contained in BiC\Aj for some i and j and such that no U contains two moves on the same unicursal path from 0 to a particular play, W. 4. For each UEiBoC^A/), U is a one-element set and there exists a probability distribution, piiu)^0, i l, 2,, j. 5. There is a pay-off function, hiw), which is an ordered pair of real numbers [hiw), h2iw) ] for each play W; hiiw) is the gain to player 1 when the result of the game is W. The family of information sets contained in Bk is denoted by %*. III. Proof of main results. To prove the main results for a general zero-sum, two-person game V, two new games, T1 and T2, are defined in which players 1 and 2 are given perfect information respectively. A relation is then established between strategies in V and those in

158 W. H. CLINGMAN [February T1 and T2 such that related strategies result in the same final outcome. Using as a starting point the fact that in a game with perfect information both players have permanently optimal strategies, the related strategies are used to determine necessary and sufficient conditions for the existence of permanently optimal strategies in T. The concept of inessential information, defined in terms of V and Tl (for player 1), plays a central role in these conditions. Given any game V, the game Tl is defined in terms of the game tree and partitions for T as follows: P1 = K, B] = Bi i = 0, 1, 2, U1 = U if U C Po or U C B2, U1 = a one element set if Ul C Pi, pi(u') = Pi(U) h)(w) = hi(w). if U C -B, The game T2 is defined in an analogous fashion with respect to player 2. A strategy for player k in T is a function rk mapping 11* into the positive integers such that UEAj implies rk(u) ^j. The function t0 maps Uo into the positive integers and is a chance strategy. The strategy rk uniquely determines the alternative chosen by player k at each move within Bk. Let Gi(t0, t.i, t2) = hi(w) be the value to player 1 of the play, W, determined by the set of strategies, (to, ti, r2). Let 3Ci(ti, t2) be the expected payoff to player 1 for the pure strategies Tl, T%. 3Ci(n, r2) = X) PiGi(ro(i), n, r,) i where 23< P* ~ 1 and Pi IS ^e probability that the chance strategy will be To(i). We now prove the following two lemmas: Lemma 1. For every pair of strategies, n and t2, in Y there is a strategy, Ti, for player 1 in V1 depending only on n, such that 3d'(t{, t2) = 3Ci(ti, t2) and Gi (r0, t{, r2) =Gi(t0, n, t2). An analogous lemma holds for T2 with the roles of the players interchanged.

1966] PERMANENTLY OPTIMAL STRATEGIES IN EXTENSIVE GAMES 159 Proof. In r1, 111 consists of one element sets and r{ is defined over these sets as follows in terms of n in T: t{ (x) = ti(17) where x E U. This definition obviously leads to the same choice of alternatives by player 1 at each move in T1 and V. Thus, the outcome, W, in T and T1 will be the same, and Since r{ is independent Gi (r0, ti, t2) = Gi(t0, of To, one also has ti, t2). Hiiri,T2) = Hiin,T2). Q.E.D. Lemma 2. For any set of strategies, (t0, n, t2) in T1, there exists a strategy Vi in Y, generally depending on t0 and t2, such that Gi (to, n, t2) = Gi(t0, 'ti, t2). Proof. Let W be the unique play determined in T1 by the set of strategies, (t0, ti, t2). Vi is defined as follows: If xe U and x is a move on the unique unicursal path from 0 to W, 'ti(17) =ti(x). If [/contains no member of this path, Vi(Z7) = 1. These two conditions are mutually exclusive, since the information set U contains at most one member of the same play. With this definition of 'n, W is the unique play determined in T by the set of strategies, (t0, Vi, t2). Gi (t, ti, t2) = Gi(t0, Vi, t2). Q.E.D. We now precisely define the concept of inessential information, which is a central part of the main results. Definition. The information withheld from player 1 in T is inessential if and only if the following is true: If the r*ii) are the pure strategies for player 1 in V, there exists a Piii) {Pi(i)=0;,Pi(i) = l} such that,- P^XiM, r2]? 3Ci [n, t2] for all n in V1 and for all t2. Piii) defines a mixed strategy for player 1 in T. We can now proceed directly to prove the following two theorems, which are the main results. Theorem 1. If the information withheld from player 1 int is inessential, then player 1 has at least one permanently optimal strategy in V. Proof. First consider the game ri = r. In the game V2 both players have perfect information. 1 has a permanently optimal strategy, fi, in J?2. Thus, player

160 W. H. CLINGMAN [February _2 _2 2 (1) JCi(fi, t,) ^ 3Ci(ti, t2) for all ti and t, in Y. Now assume that t* is a strategy for player 2 in T and that 3Ci(ti, t*) <3Ci(ti, t*) for some ti in the game P. By Lemma 1, however, we can define the strategy t*2 in f2 such that 3Ci(fi, r 2) <3C2i(ti, t*2). This contradicts (1). Thus (2) 3Ci(f i, t2*) ^ 3Ci(ti, t2*) for all tx and t2* in the game T. Thus, player 1 has a permanently optimal strategy, fi, in the game r^r. Since the information withheld from player 1 in T is inessential, there exists a Pi(i) such that (3) E Pi(i)Ki[rf(i), t2*] ^ 3Ci[f,, r2*] for all r2*. Then there is an a such that 3Ci[n*(a), r2*] ^ 3Ci[f,, t2*] ^ 3Ci(n, t2*) for all t* and all n in the game T. Assume that player 1 does not have a permanently optimal strategy in r. Then T*(a) is not permanently optimal, and there exist a r*(b) and a t*(c) such that 3Ci[T*(a), t%(c)] <5Ci[t*(b), t*(c)]. From Lemma 1 strategies T*'(a) and T*'(b) can be defined for player 1 in T such that (4) 3Ci[ri*'(a), t2*] ^ 3t5i(n, t2*) for all r2* and n in V and (5) 3Ci[n*'(a), r2*(c)] < 3Ci[n*'(6), r2*(c)]. (4) and (5) are contradictory, proving the theorem. Q.E.D. Theorem 2. If the game T contains no chance moves and if player 1 has a permanently optimal strategy in T, then the information withheld from player 1 is inessential. Proof. Let t? be a permanently optimal strategy for player 1 in V. Now assume that the information withheld from player 1 in V is essential. Then there exists a Ti(a) in T1 and a T2(b) such that Ki[r i, r2(b)]<3c{ [Ti(a), T2(b)]. Since the game contains no chance moves, Lemma 2 is valid for the

i966] PERMANENTLY OPTIMAL STRATEGIES IN EXTENSIVE GAMES 161 functions 3C/ and 3Ci. A strategy Vi(a) in T can be defined such that: 3Ci[Vi, t,(6)] =Xi [nia), nib)]. Thus, 3Ci[t, t2(6) ] < 3Ci ['n, t2(&)]. This last inequality contradicts the premise that t is a permanently optimal strategy, thus proving the theorem. Q.E.D. Bibliography 1. H. W. Kuhn, Contributions to the theory of games, Vol. 2, Princeton Univ. Press, Princeton, N. J., 1953; pp. 193-216. 2. J. von Neumann and O. Morgenstern, Theory of games and economic behavior, Princeton Univ. Press, Princeton, N. J., 1947. 3. N. Dalkey, Contributions to the theory of games, Vol. 2, Princeton Univ. Press, Princeton, N. J., 1953; pp. 217-243. Texas Instruments Incorporated, Dallas, Texas