Extensive Form Games

Total Page:16

File Type:pdf, Size:1020Kb

Extensive Form Games The Extensive Form Backward Induction Subgame Perfect Equilibrium Lecture 24 Extensive Form Games Jitesh H. Panchal ME 597: Decision Making for Engineering Systems Design Design Engineering Lab @ Purdue (DELP) School of Mechanical Engineering Purdue University, West Lafayette, IN http://engineering.purdue.edu/delp November 14, 2019 ME 597: Fall 2019 Lecture 24 1 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Lecture Outline 1 The Extensive Form 2 Backward Induction Examples 3 Subgame Perfect Equilibrium Definition Examples Dutta, P.K. (1999). Strategies and Games: Theory and Practice. Cambridge, MA, The MIT Press. Chapters 11-13. ME 597: Fall 2019 Lecture 24 2 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Game Tree A Game Tree Decision Node: Point in the game where one player–and only one player–has to make a decision. Branch: Each branch corresponds to one of the choices. Root: Starting point of the tree. Terminal node: No branches emanating from it. Figure: 11.1 on Page 158 (Dutta) ME 597: Fall 2019 Lecture 24 3 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Game tree Information set (oval) represents simultaneous moves. It represents nodes that are indistinguishable from the decision maker’s standpoint. Figure: 11.2 on Page 159 (Dutta) ME 597: Fall 2019 Lecture 24 4 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Consistency Requirements 1 Single starting point 2 No cycles 3 One way to proceed: There must not be two or more branches leading to a node. ME 597: Fall 2019 Lecture 24 5 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Strategies A player’s strategy is a complete, conditional plan of action. Complete: what to choose at every relevant decision node. Conditional: which branch to follow out of a decision node if the game arrives at that node. ME 597: Fall 2019 Lecture 24 6 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Mixed Strategies Same as in strategic form: a probability distribution over the pure strategies. ME 597: Fall 2019 Lecture 24 7 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Chance Nodes Chance node: Nodes whose branches represent several random possibilities. Used to represent uncertainty inherent in the game (as opposed to uncertainty introduced by players through mixed strategies.) Figure: 11.5 on Page 162 (Dutta) ME 597: Fall 2019 Lecture 24 8 / 31 The Extensive Form Backward Induction Subgame Perfect Equilibrium Perfect Information Games Definition (Perfect Information Game) A game of perfect information is one in which there is no information set (with multiple nodes). Any time a player has to move, he/she knows exactly the entire history of choices made by all previous players. Game of perfect information cannot have any simultaneous moves. ME 597: Fall 2019 Lecture 24 9 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Basic Idea: Sequential Rationality Rationality: Each player picks the best action available to him at a decision node, given what he thinks is going to be the future play of the game. Sequential: Players will infer what the future is going to be knowing that, in the future, players will reason in the same way. ME 597: Fall 2019 Lecture 24 10 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example - Entry Game Every strategy has three components (e.g., EAT). Figure: 11.7 on Page 164 (Dutta) ME 597: Fall 2019 Lecture 24 11 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example – Entry Game (contd.) Strategic form: Coke / Pepsi TA ETT −2; −1 0; −3 ETA −2; −1 1; 2 EAT −3; 1 0; −3 EAA −3; 1 1; 2 OTT 0; 5 0; 5 OTA 0; 5 0; 5 OAT 0; 5 0; 5 OAA 0; 5 0; 5 How many pure strategy Nash equilibria does this game have? ME 597: Fall 2019 Lecture 24 12 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Pure Strategy Nash Equilibria 1 Pepsi: T ; Coke: OTT ; OTA; OAT , or OAA 2 Pepsi: A; Coke: ETA 3 Pepsi: A; Coke: EAA The only sequentially rational strategy is: Pepsi: A; Coke: ETA ME 597: Fall 2019 Lecture 24 13 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Backward Induction: General Result Kuhn’s Theorem Every game of perfect information with a finite number of nodes has a solution to backward induction. Indeed, if for every player it is the case that no two payoffs are the same, then there is a unique solution to backward induction. Fold the decision tree back one step at a time till we reach the beginning. Proof by Induction... ME 597: Fall 2019 Lecture 24 14 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Backward Induction: Equivalent to IEDS in the strategic form Example: Coke / Pepsi TA ETT −2; −1 0; −3 ETA −2; −1 1; 2 EAT −3; 1 0; −3 EAA −3; 1 1; 2 OTT 0; 5 0; 5 OTA 0; 5 0; 5 OAT 0; 5 0; 5 OAA 0; 5 0; 5 ME 597: Fall 2019 Lecture 24 15 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Another Example Figure: 11.13 on Page 173 (Dutta) ME 597: Fall 2019 Lecture 24 16 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: Research and Development Questions of interest: How much should each firm spend on R&D, and how often? When should it get into the race, and at what point should it opt out of such a race? What factors determine the likely winner: is it an advantage to be in a related manufacturing area, is it more important to have a superior R&D department, and so on? ME 597: Fall 2019 Lecture 24 17 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Suppose there are two firms: RCA (R) and Sony (S) Simplifying assumptions: 1 The distance from the eventual goal can be measured; we can say, for example, that firm S is n steps from completing the project. 2 Either firm can move 1, 2, or 3 steps closer to the end in any one period. 3 It costs $2 to move one step forward, $7 to move two steps forward, and $15 to move three steps forward. 4 Whichever firm completes all the steps first gets the patent; the patent is worth $20. 5 The firms take turns deciding how much to spend on R&D; if RCA makes an R&D decision this period, it waits to make any further decisions till it learns of Sony’s next R&D commitment. Furthermore, Sony makes its announcement in the period following RCA’s announcement. ME 597: Fall 2019 Lecture 24 18 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Figure: 12.1 on Page 183 (Dutta) ME 597: Fall 2019 Lecture 24 19 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Figure: 12.2 on Page 184 (Dutta) ME 597: Fall 2019 Lecture 24 20 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Figure: 12.3 on Page 185 (Dutta) ME 597: Fall 2019 Lecture 24 21 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Figure: 12.4 on Page 186 (Dutta) ME 597: Fall 2019 Lecture 24 22 / 31 The Extensive Form Backward Induction Examples Subgame Perfect Equilibrium Example: A Model of Research and Development Figure: 12.5 on Page 187 (Dutta) ME 597: Fall 2019 Lecture 24 23 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgames Game of Imperfect Information: Game in extensive form that is not a game of perfect information. Definition (Subgame) A subgame is a part of the extensive form: it is a collection of nodes and branches that satisfies three properties: 1 It starts at a single decision node. 2 It contains every successor to this node. 3 If it contains any part of an information set, then it contains all the nodes in that information set. Once you are in a subgame, you cannot stray out of it. You will have all the information within the subgame to make decisions. ME 597: Fall 2019 Lecture 24 24 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgames – Examples Not sub-games: Figure: 13.2-13.4 on Page 197 (Dutta) ME 597: Fall 2019 Lecture 24 25 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgame Perfect Equilibrium s1 and s2 constitute a subgame perfect (Nash) equilibrium if for every subgame g, s1(g) and s2(g) constitute a Nash equilibrium within the subgame. ME 597: Fall 2019 Lecture 24 26 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgame Perfect Equilibrium In a game of perfect information, the subgame perfect equilibria are precisely the backward induction solutions. Hence, whenever the backward induction solution is unique, there is a single subgame perfect equilibrium. ME 597: Fall 2019 Lecture 24 27 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgame Perfect Equilibrium – Example Once repeated Prisoner’s Dilemma ME 597: Fall 2019 Figure: 13.5 on PageLecture 199 24 (Dutta) 28 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Subgame Perfect Equilibrium – Example Voting Figure: 13.6 on Page 201 (Dutta) ME 597: Fall 2019 Lecture 24 29 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium Summary 1 The Extensive Form 2 Backward Induction Examples 3 Subgame Perfect Equilibrium Definition Examples ME 597: Fall 2019 Lecture 24 30 / 31 The Extensive Form Definition Backward Induction Examples Subgame Perfect Equilibrium References 1 Dutta, P.K.
Recommended publications
  • Lecture 4 Rationalizability & Nash Equilibrium Road
    Lecture 4 Rationalizability & Nash Equilibrium 14.12 Game Theory Muhamet Yildiz Road Map 1. Strategies – completed 2. Quiz 3. Dominance 4. Dominant-strategy equilibrium 5. Rationalizability 6. Nash Equilibrium 1 Strategy A strategy of a player is a complete contingent-plan, determining which action he will take at each information set he is to move (including the information sets that will not be reached according to this strategy). Matching pennies with perfect information 2’s Strategies: HH = Head if 1 plays Head, 1 Head if 1 plays Tail; HT = Head if 1 plays Head, Head Tail Tail if 1 plays Tail; 2 TH = Tail if 1 plays Head, 2 Head if 1 plays Tail; head tail head tail TT = Tail if 1 plays Head, Tail if 1 plays Tail. (-1,1) (1,-1) (1,-1) (-1,1) 2 Matching pennies with perfect information 2 1 HH HT TH TT Head Tail Matching pennies with Imperfect information 1 2 1 Head Tail Head Tail 2 Head (-1,1) (1,-1) head tail head tail Tail (1,-1) (-1,1) (-1,1) (1,-1) (1,-1) (-1,1) 3 A game with nature Left (5, 0) 1 Head 1/2 Right (2, 2) Nature (3, 3) 1/2 Left Tail 2 Right (0, -5) Mixed Strategy Definition: A mixed strategy of a player is a probability distribution over the set of his strategies. Pure strategies: Si = {si1,si2,…,sik} σ → A mixed strategy: i: S [0,1] s.t. σ σ σ i(si1) + i(si2) + … + i(sik) = 1. If the other players play s-i =(s1,…, si-1,si+1,…,sn), then σ the expected utility of playing i is σ σ σ i(si1)ui(si1,s-i) + i(si2)ui(si2,s-i) + … + i(sik)ui(sik,s-i).
    [Show full text]
  • 1 Sequential Games
    1 Sequential Games We call games where players take turns moving “sequential games”. Sequential games consist of the same elements as normal form games –there are players, rules, outcomes, and payo¤s. However, sequential games have the added element that history of play is now important as players can make decisions conditional on what other players have done. Thus, if two people are playing a game of Chess the second mover is able to observe the …rst mover’s initial move prior to making his initial move. While it is possible to represent sequential games using the strategic (or matrix) form representation of the game it is more instructive at …rst to represent sequential games using a game tree. In addition to the players, actions, outcomes, and payo¤s, the game tree will provide a history of play or a path of play. A very basic example of a sequential game is the Entrant-Incumbent game. The game is described as follows: Consider a game where there is an entrant and an incumbent. The entrant moves …rst and the incumbent observes the entrant’sdecision. The entrant can choose to either enter the market or remain out of the market. If the entrant remains out of the market then the game ends and the entrant receives a payo¤ of 0 while the incumbent receives a payo¤ of 2. If the entrant chooses to enter the market then the incumbent gets to make a choice. The incumbent chooses between …ghting entry or accommodating entry. If the incumbent …ghts the entrant receives a payo¤ of 3 while the incumbent receives a payo¤ of 1.
    [Show full text]
  • Lecture Notes
    GRADUATE GAME THEORY LECTURE NOTES BY OMER TAMUZ California Institute of Technology 2018 Acknowledgments These lecture notes are partially adapted from Osborne and Rubinstein [29], Maschler, Solan and Zamir [23], lecture notes by Federico Echenique, and slides by Daron Acemoglu and Asu Ozdaglar. I am indebted to Seo Young (Silvia) Kim and Zhuofang Li for their help in finding and correcting many errors. Any comments or suggestions are welcome. 2 Contents 1 Extensive form games with perfect information 7 1.1 Tic-Tac-Toe ........................................ 7 1.2 The Sweet Fifteen Game ................................ 7 1.3 Chess ............................................ 7 1.4 Definition of extensive form games with perfect information ........... 10 1.5 The ultimatum game .................................. 10 1.6 Equilibria ......................................... 11 1.7 The centipede game ................................... 11 1.8 Subgames and subgame perfect equilibria ...................... 13 1.9 The dollar auction .................................... 14 1.10 Backward induction, Kuhn’s Theorem and a proof of Zermelo’s Theorem ... 15 2 Strategic form games 17 2.1 Definition ......................................... 17 2.2 Nash equilibria ...................................... 17 2.3 Classical examples .................................... 17 2.4 Dominated strategies .................................. 22 2.5 Repeated elimination of dominated strategies ................... 22 2.6 Dominant strategies ..................................
    [Show full text]
  • SEQUENTIAL GAMES with PERFECT INFORMATION Example
    SEQUENTIAL GAMES WITH PERFECT INFORMATION Example 4.9 (page 105) Consider the sequential game given in Figure 4.9. We want to apply backward induction to the tree. 0 Vertex B is owned by player two, P2. The payoffs for P2 are 1 and 3, with 3 > 1, so the player picks R . Thus, the payoffs at B become (0, 3). 00 Next, vertex C is also owned by P2 with payoffs 1 and 0. Since 1 > 0, P2 picks L , and the payoffs are (4, 1). Player one, P1, owns A; the choice of L gives a payoff of 0 and R gives a payoff of 4; 4 > 0, so P1 chooses R. The final payoffs are (4, 1). 0 00 We claim that this strategy profile, { R } for P1 and { R ,L } is a Nash equilibrium. Notice that the 0 00 strategy profile gives a choice at each vertex. For the strategy { R ,L } fixed for P2, P1 has a maximal payoff by choosing { R }, ( 0 00 0 00 π1(R, { R ,L }) = 4 π1(R, { R ,L }) = 4 ≥ 0 00 π1(L, { R ,L }) = 0. 0 00 In the same way, for the strategy { R } fixed for P1, P2 has a maximal payoff by choosing { R ,L }, ( 00 0 00 π2(R, {∗,L }) = 1 π2(R, { R ,L }) = 1 ≥ 00 π2(R, {∗,R }) = 0, where ∗ means choose either L0 or R0. Since no change of choice by a player can increase that players own payoff, the strategy profile is called a Nash equilibrium. Notice that the above strategy profile is also a Nash equilibrium on each branch of the game tree, mainly starting at either B or starting at C.
    [Show full text]
  • 1 Bertrand Model
    ECON 312: Oligopolisitic Competition 1 Industrial Organization Oligopolistic Competition Both the monopoly and the perfectly competitive market structure has in common is that neither has to concern itself with the strategic choices of its competition. In the former, this is trivially true since there isn't any competition. While the latter is so insignificant that the single firm has no effect. In an oligopoly where there is more than one firm, and yet because the number of firms are small, they each have to consider what the other does. Consider the product launch decision, and pricing decision of Apple in relation to the IPOD models. If the features of the models it has in the line up is similar to Creative Technology's, it would have to be concerned with the pricing decision, and the timing of its announcement in relation to that of the other firm. We will now begin the exposition of Oligopolistic Competition. 1 Bertrand Model Firms can compete on several variables, and levels, for example, they can compete based on their choices of prices, quantity, and quality. The most basic and funda- mental competition pertains to pricing choices. The Bertrand Model is examines the interdependence between rivals' decisions in terms of pricing decisions. The assumptions of the model are: 1. 2 firms in the market, i 2 f1; 2g. 2. Goods produced are homogenous, ) products are perfect substitutes. 3. Firms set prices simultaneously. 4. Each firm has the same constant marginal cost of c. What is the equilibrium, or best strategy of each firm? The answer is that both firms will set the same prices, p1 = p2 = p, and that it will be equal to the marginal ECON 312: Oligopolisitic Competition 2 cost, in other words, the perfectly competitive outcome.
    [Show full text]
  • Economics 201B Economic Theory (Spring 2021) Strategic Games
    Economics 201B Economic Theory (Spring 2021) Strategic Games Topics: terminology and notations (OR 1.7), games and solutions (OR 1.1-1.3), rationality and bounded rationality (OR 1.4-1.6), formalities (OR 2.1), best-response (OR 2.2), Nash equilibrium (OR 2.2), 2 2 examples × (OR 2.3), existence of Nash equilibrium (OR 2.4), mixed strategy Nash equilibrium (OR 3.1, 3.2), strictly competitive games (OR 2.5), evolution- ary stability (OR 3.4), rationalizability (OR 4.1), dominance (OR 4.2, 4.3), trembling hand perfection (OR 12.5). Terminology and notations (OR 1.7) Sets For R, ∈ ≥ ⇐⇒ ≥ for all . and ⇐⇒ ≥ for all and some . ⇐⇒ for all . Preferences is a binary relation on some set of alternatives R. % ⊆ From % we derive two other relations on : — strict performance relation and not  ⇐⇒ % % — indifference relation and ∼ ⇐⇒ % % Utility representation % is said to be — complete if , or . ∀ ∈ % % — transitive if , and then . ∀ ∈ % % % % can be presented by a utility function only if it is complete and transitive (rational). A function : R is a utility function representing if → % ∀ ∈ () () % ⇐⇒ ≥ % is said to be — continuous (preferences cannot jump...) if for any sequence of pairs () with ,and and , . { }∞=1 % → → % — (strictly) quasi-concave if for any the upper counter set ∈ { ∈ : is (strictly) convex. % } These guarantee the existence of continuous well-behaved utility function representation. Profiles Let be a the set of players. — () or simply () is a profile - a collection of values of some variable,∈ one for each player. — () or simply is the list of elements of the profile = ∈ { } − () for all players except . ∈ — ( ) is a list and an element ,whichistheprofile () .
    [Show full text]
  • Chapter 16 Oligopoly and Game Theory Oligopoly Oligopoly
    Chapter 16 “Game theory is the study of how people Oligopoly behave in strategic situations. By ‘strategic’ we mean a situation in which each person, when deciding what actions to take, must and consider how others might respond to that action.” Game Theory Oligopoly Oligopoly • “Oligopoly is a market structure in which only a few • “Figuring out the environment” when there are sellers offer similar or identical products.” rival firms in your market, means guessing (or • As we saw last time, oligopoly differs from the two ‘ideal’ inferring) what the rivals are doing and then cases, perfect competition and monopoly. choosing a “best response” • In the ‘ideal’ cases, the firm just has to figure out the environment (prices for the perfectly competitive firm, • This means that firms in oligopoly markets are demand curve for the monopolist) and select output to playing a ‘game’ against each other. maximize profits • To understand how they might act, we need to • An oligopolist, on the other hand, also has to figure out the understand how players play games. environment before computing the best output. • This is the role of Game Theory. Some Concepts We Will Use Strategies • Strategies • Strategies are the choices that a player is allowed • Payoffs to make. • Sequential Games •Examples: • Simultaneous Games – In game trees (sequential games), the players choose paths or branches from roots or nodes. • Best Responses – In matrix games players choose rows or columns • Equilibrium – In market games, players choose prices, or quantities, • Dominated strategies or R and D levels. • Dominant Strategies. – In Blackjack, players choose whether to stay or draw.
    [Show full text]
  • Dynamic Games Under Bounded Rationality
    Munich Personal RePEc Archive Dynamic Games under Bounded Rationality Zhao, Guo Southwest University for Nationalities 8 March 2015 Online at https://mpra.ub.uni-muenchen.de/62688/ MPRA Paper No. 62688, posted 09 Mar 2015 08:52 UTC Dynamic Games under Bounded Rationality By ZHAO GUO I propose a dynamic game model that is consistent with the paradigm of bounded rationality. Its main advantages over the traditional approach based on perfect rationality are that: (1) the strategy space is a chain-complete partially ordered set; (2) the response function is certain order-preserving map on strategy space; (3) the evolution of economic system can be described by the Dynamical System defined by the response function under iteration; (4) the existence of pure-strategy Nash equilibria can be guaranteed by fixed point theorems for ordered structures, rather than topological structures. This preference-response framework liberates economics from the utility concept, and constitutes a marriage of normal-form and extensive-form games. Among the common assumptions of classical existence theorems for competitive equilibrium, one is central. That is, individuals are assumed to have perfect rationality, so as to maximize their utilities (payoffs in game theoretic usage). With perfect rationality and perfect competition, the competitive equilibrium is completely determined, and the equilibrium depends only on their goals and their environments. With perfect rationality and perfect competition, the classical economic theory turns out to be deductive theory that requires almost no contact with empirical data once its assumptions are accepted as axioms (see Simon 1959). Zhao: Southwest University for Nationalities, Chengdu 610041, China (e-mail: [email protected]).
    [Show full text]
  • Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction
    Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction Renato Paes Leme Eva´ Tardos Department of Computer Science Department of Computer Science Cornell University, Ithaca, NY Cornell University, Ithaca, NY [email protected] [email protected] Abstract—The Generalized Second Price Auction has for advertisements and slots higher on the page are been the main mechanism used by search companies more valuable (clicked on by more users). The bids to auction positions for advertisements on search pages. are used to determine both the assignment of bidders In this paper we study the social welfare of the Nash equilibria of this game in various models. In the full to slots, and the fees charged. In the simplest model, information setting, socially optimal Nash equilibria are the bidders are assigned to slots in order of bids, and known to exist (i.e., the Price of Stability is 1). This paper the fee for each click is the bid occupying the next is the first to prove bounds on the price of anarchy, and slot. This auction is called the Generalized Second Price to give any bounds in the Bayesian setting. Auction (GSP). More generally, positions and payments Our main result is to show that the price of anarchy is small assuming that all bidders play un-dominated in the Generalized Second Price Auction depend also on strategies. In the full information setting we prove a bound the click-through rates associated with the bidders, the of 1.618 for the price of anarchy for pure Nash equilibria, probability that the advertisement will get clicked on by and a bound of 4 for mixed Nash equilibria.
    [Show full text]
  • Extensive Form Games with Perfect Information
    Notes Strategy and Politics: Extensive Form Games with Perfect Information Matt Golder Pennsylvania State University Sequential Decision-Making Notes The model of a strategic (normal form) game suppresses the sequential structure of decision-making. When applying the model to situations in which players move sequentially, we assume that each player chooses her plan of action once and for all. She is committed to this plan, which she cannot modify as events unfold. The model of an extensive form game, by contrast, describes the sequential structure of decision-making explicitly, allowing us to study situations in which each player is free to change her mind as events unfold. Perfect Information Notes Perfect information describes a situation in which players are always fully informed about all of the previous actions taken by all players. This assumption is used in all of the following lecture notes that use \perfect information" in the title. Later we will also study more general cases where players may only be imperfectly informed about previous actions when choosing an action. Extensive Form Games Notes To describe an extensive form game with perfect information we need to specify the set of players and their preferences, just as for a strategic game. In addition, we also need to specify the order of the players' moves and the actions each player may take at each point (or decision node). We do so by specifying the set of all sequences of actions that can possibly occur, together with the player who moves at each point in each sequence. We refer to each possible sequence of actions (a1; a2; : : : ak) as a terminal history and to the function that denotes the player who moves at each point in each terminal history as the player function.
    [Show full text]
  • UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society
    UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title Language as a Tool for Thought: The Vocabulary of Games Facilitates Strategic Decision Making Permalink https://escholarship.org/uc/item/2n8028tv Journal Proceedings of the Annual Meeting of the Cognitive Science Society, 28(28) ISSN 1069-7977 Authors Keller, Josh Loewenstein, Jeffrey Publication Date 2006 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Language as a Tool for Thought: The Vocabulary of Games Facilitates Strategic Decision Making Jeffrey Loewenstein ([email protected]) McCombs School of Business, 1 University Station B6300 Austin, TX 78712 USA Josh Keller ([email protected]) McCombs School of Business, 1 University Station B6300 Austin, TX 78712 USA Abstract thereby influence key decision makers to favor their desired policies. More than 60 years ago, the sociologist Mills People in competitive decision-making situations often make (1939) argued that problems are perceived relative to a poor choices because they inadequately understand the vocabulary. For example, what counts as murder seems decision they are to make, particularly because they fail to straightforward, but should differ substantially across consider contingencies such as how their opponent will react vegans, anti-abortion activists, lawyers, soldiers and the to their choice (Tor & Bazerman, 2004). Accordingly it would be useful to have a generally applicable vocabulary to guide (hopefully extinct) ritual practitioner of human sacrifice people towards effective interpretations of decision situations. (Clark, 1998). The vocabulary of games provides one such toolkit. We One role of language is to invoke particular framings or presented 508 participants with words from the vocabulary of interpretations.
    [Show full text]
  • Games with Hidden Information
    Games with Hidden Information R&N Chapter 6 R&N Section 17.6 • Assumptions so far: – Two-player game : Player A and B. – Perfect information : Both players see all the states and decisions. Each decision is made sequentially . – Zero-sum : Player’s A gain is exactly equal to player B’s loss. • We are going to eliminate these constraints. We will eliminate first the assumption of “perfect information” leading to far more realistic models. – Some more game-theoretic definitions Matrix games – Minimax results for perfect information games – Minimax results for hidden information games 1 Player A 1 L R Player B 2 3 L R L R Player A 4 +2 +5 +2 L Extensive form of game: Represent the -1 +4 game by a tree A pure strategy for a player 1 defines the move that the L R player would make for every possible state that the player 2 3 would see. L R L R 4 +2 +5 +2 L -1 +4 2 Pure strategies for A: 1 Strategy I: (1 L,4 L) Strategy II: (1 L,4 R) L R Strategy III: (1 R,4 L) Strategy IV: (1 R,4 R) 2 3 Pure strategies for B: L R L R Strategy I: (2 L,3 L) Strategy II: (2 L,3 R) 4 +2 +5 +2 Strategy III: (2 R,3 L) L R Strategy IV: (2 R,3 R) -1 +4 In general: If N states and B moves, how many pure strategies exist? Matrix form of games Pure strategies for A: Pure strategies for B: Strategy I: (1 L,4 L) Strategy I: (2 L,3 L) Strategy II: (1 L,4 R) Strategy II: (2 L,3 R) Strategy III: (1 R,4 L) Strategy III: (2 R,3 L) 1 Strategy IV: (1 R,4 R) Strategy IV: (2 R,3 R) R L I II III IV 2 3 L R I -1 -1 +2 +2 L R 4 II +4 +4 +2 +2 +2 +5 +1 L R III +5 +1 +5 +1 IV +5 +1 +5 +1 -1 +4 3 Pure strategies for Player B Player A’s payoff I II III IV if game is played I -1 -1 +2 +2 with strategy I by II +4 +4 +2 +2 Player A and strategy III by III +5 +1 +5 +1 Player B for Player A for Pure strategies IV +5 +1 +5 +1 • Matrix normal form of games: The table contains the payoffs for all the possible combinations of pure strategies for Player A and Player B • The table characterizes the game completely, there is no need for any additional information about rules, etc.
    [Show full text]