scholarly journals The State of Solving Large Incomplete-Information Games, and Application to Poker

AI Magazine ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 13 ◽  
Author(s):  
Tuomas Sandholm
Keyword(s):  
Incomplete Information ◽  
The State ◽  
Solution Concepts ◽  
Security Applications ◽  
Incomplete Information Games ◽  
Game Theoretic ◽  
Theoretic Solution ◽  
Information Games

Game-theoretic solution concepts prescribe how rational parties should act, but to become operational the concepts need to be accompanied by algorithms. I will review the state of solving incomplete-information games. They encompass many practical problems such as auctions, negotiations, and security applications. I will discuss them in the context of how they have transformed computer poker. In short, game-theoretic reasoning now scales to many large problems, outperforms the alternatives on those problems, and in some games beats the best humans.

scholarly journals Team Production and Esteem: A Dual Selves Model with Belief-Dependent Preferences

Games ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 33
Author(s):  
Matthias Greiff
Keyword(s):  
Game Theory ◽  
Incomplete Information ◽  
Affective Responses ◽  
Team Production ◽  
Solution Concepts ◽  
Game Theoretic ◽  
Psychological Game Theory ◽  
Expression Of Emotions ◽  
Theoretic Solution ◽  
High Effort

We propose a dual selves model to integrate affective responses and belief-dependent emotions into game theory. We apply our model to team production and model a worker as being composed of a rational self, who chooses effort, and an emotional self, who expresses esteem. Similar to psychological game theory, utilities depend on beliefs, but only indirectly. More concretely, emotions affect utilities, and the expression of emotions depends on updated beliefs. Modeling affective responses as actions chosen by the emotional self allows us to apply standard game-theoretic solution concepts. The model reveals that with incomplete information about abilities, workers only choose high effort if esteem is expressed based on interpersonal comparisons and if the preference for esteem is a status preference.

Strategic Interaction and Interstate Crises: A Bayesian Quantal Response Estimator for Incomplete Information Games

2008 ◽  
Vol 16 (3) ◽  
pp. 250-273 ◽  
Author(s):  
Justin Esarey ◽  
Bumba Mukherjee ◽  
Will H. Moore
Keyword(s):  
Asymmetric Information ◽  
Incomplete Information ◽  
Learning Process ◽  
Private Information ◽  
Statistical Treatment ◽  
Quantal Response ◽  
Crisis Bargaining ◽  
Incomplete Information Games ◽  
Information Characteristics ◽  
Information Games

Private information characteristics like resolve and audience costs are powerful influences over strategic international behavior, especially crisis bargaining. As a consequence, states face asymmetric information when interacting with one another and will presumably try to learn about each others' private characteristics by observing each others' behavior. A satisfying statistical treatment would account for the existence of asymmetric information and model the learning process. This study develops a formal and statistical framework for incomplete information games that we term the Bayesian Quantal Response Equilibrium Model (BQRE model). Our BQRE model offers three advantages over existing work: it directly incorporates asymmetric information into the statistical model's structure, estimates the influence of private information characteristics on behavior, and mimics the temporal learning process that we believe takes place in international politics.

scholarly journals Efficient Computation of Semivalues for Game-Theoretic Network Centrality

2018 ◽  
Vol 63 ◽  
pp. 145-189 ◽  
Author(s):  
Mateusz K. Tarkowski ◽  
Piotr L. Szczepański ◽  
Tomasz P. Michalak ◽  
Paul Harrenstein ◽  
Michael Wooldridge
Keyword(s):  
Polynomial Time ◽  
Shapley Value ◽  
Centrality Measures ◽  
Efficient Computation ◽  
Solution Concepts ◽  
Banzhaf Index ◽  
The Shapley Value ◽  
Game Theoretic ◽  
Theoretic Solution ◽  
Network Centralities

Some game-theoretic solution concepts such as the Shapley value and the Banzhaf index have recently gained popularity as measures of node centrality in networks. While this direction of research is promising, the computational problems that surround it are challenging and have largely been left open. To date there are only a few positive results in the literature, which show that some game-theoretic extensions of degree-, closeness- and betweenness-centrality measures are computable in polynomial time, i.e., without the need to enumerate the exponential number of all possible coalitions. In this article, we show that these results can be extended to a much larger class of centrality measures that are based on a family of solution concepts known as semivalues. The family of semivalues includes, among others, the Shapley value and the Banzhaf index. To this end, we present a generic framework for defining game-theoretic network centralities and prove that all centrality measures that can be expressed in this framework are computable in polynomial time. Using our framework, we present a number of new and polynomial-time computable game-theoretic centrality measures.

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