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Winners-take-all situations introduce an incentive for agents to diversify their behavior, since doing so will result in splitting an eventual price with fewer people. At the same time, when the payoff of a process depends on a parameter…

Computer Science and Game Theory · Computer Science 2019-06-11 Abel Molina

In this paper, we consider two-player zero-sum matrix and stochastic games and develop learning dynamics that are payoff-based, convergent, rational, and symmetric between the two players. Specifically, the learning dynamics for matrix…

Machine Learning · Computer Science 2024-09-06 Zaiwei Chen , Kaiqing Zhang , Eric Mazumdar , Asuman Ozdaglar , Adam Wierman

Online learning algorithms that minimize regret provide strong guarantees in situations that involve repeatedly making decisions in an uncertain environment, e.g. a driver deciding what route to drive to work every day. While regret…

Computer Science and Game Theory · Computer Science 2013-09-06 Jeremiah Blocki , Nicolas Christin , Anupam Datta , Arunesh Sinha

Systematic discriminatory biases present in our society influence the way data is collected and stored, the way variables are defined, and the way scientific findings are put into practice as policy. Automated decision procedures and…

Machine Learning · Computer Science 2019-05-29 Razieh Nabi , Daniel Malinsky , Ilya Shpitser

At a mixed Nash equilibrium, the payoff of a player does not depend on her own action, as long as her opponent sticks to his. In a periodic strategy, a concept developed in a previous paper (arXiv:1307.2035v4), in contrast, the own payoff…

Computer Science and Game Theory · Computer Science 2020-05-27 V. K. Oikonomou , J. Jost

Two players alternate tossing a biased coin where the probability of getting heads is p. The current player is awarded alpha points for tails and alpha+beta for heads. The first player reaching n points wins. For a completely unfair coin…

Probability · Mathematics 2011-12-15 Robert W. Chen , Burton Rosenberg

We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the…

Computer Science and Game Theory · Computer Science 2022-03-29 Hugo Gimbert , Edon Kelmendi

This paper proposes a game-theoretic approach to address the problem of optimal sensor placement against an adversary in uncertain networked control systems. The problem is formulated as a zero-sum game with two players, namely a malicious…

Systems and Control · Electrical Eng. & Systems 2023-01-13 Anh Tung Nguyen , Sribalaji C. Anand , André M. H. Teixeira

We all have preferences when multiple choices are available. If we insist on satisfying our preferences only, we may suffer a loss due to conflicts with other people's identical selections. Such a case applies when the choice cannot be…

Theoretical Economics · Economics 2023-02-21 Hiroaki Shinkawa , Nicolas Chauvet , Guillaume Bachelier , André Röhm , Ryoichi Horisaki , Makoto Naruse

We study a repeated game with payoff externalities and observable actions where two players receive information over time about an underlying payoff-relevant state, and strategically coordinate their actions. Players learn about the true…

Theoretical Economics · Economics 2018-09-05 Pathikrit Basu , Kalyan Chatterjee , Tetsuya Hoshino , Omer Tamuz

In this paper, $2\times2$ zero-sum games are studied under the following assumptions: $(1)$ One of the players (the leader) commits to choose its actions by sampling a given probability measure (strategy); $(2)$ The leader announces its…

Computer Science and Game Theory · Computer Science 2023-05-12 Ke Sun , Samir M. Perlaza , Alain Jean-Marie

This paper studies the optimization of strategies in the context of possibly randomized two players zero-sum games with incomplete information. We compare 5 algorithms for tuning the parameters of strategies over a benchmark of 12 games. A…

Computer Science and Game Theory · Computer Science 2018-07-06 Marie-Liesse Cauwet , Olivier Teytaud

Learning from repeated play in a fixed two-player zero-sum game is a classic problem in game theory and online learning. We consider a variant of this problem where the game payoff matrix changes over time, possibly in an adversarial…

Machine Learning · Computer Science 2022-02-01 Mengxiao Zhang , Peng Zhao , Haipeng Luo , Zhi-Hua Zhou

The combination of the Bayesian game and learning has a rich history, with the idea of controlling a single agent in a system composed of multiple agents with unknown behaviors given a set of types, each specifying a possible behavior for…

Machine Learning · Computer Science 2024-11-21 Tongxin Li , Tinashe Handina , Shaolei Ren , Adam Wierman

Deception plays a key role in adversarial or strategic interactions for the purpose of self-defence and survival. This paper introduces a general framework and solution to address deception. Most existing approaches for deception consider…

Artificial Intelligence · Computer Science 2019-04-26 Bo Wu , Murat Cubuktepe , Suda Bharadwaj , Ufuk Topcu

We study the problem of repeated play in a zero-sum game in which the payoff matrix may change, in a possibly adversarial fashion, on each round; we call these Online Matrix Games. Finding the Nash Equilibrium (NE) of a two player zero-sum…

Machine Learning · Computer Science 2020-04-06 Adrian Rivera Cardoso , Jacob Abernethy , He Wang , Huan Xu

Fighting Fantasy is a popular recreational fantasy gaming system worldwide. Combat in this system progresses through a stochastic game involving a series of rounds, each of which may be won or lost. Each round, a limited resource (`luck')…

Artificial Intelligence · Computer Science 2020-02-25 Iain G. Johnston

Strategic decision-making in uncertain and adversarial environments is crucial for the security of modern systems and infrastructures. A salient feature of many optimal decision-making policies is a level of unpredictability, or randomness,…

Computer Science and Game Theory · Computer Science 2024-05-03 Keith Paarporn , Rahul Chandan , Dan Kovenock , Mahnoosh Alizadeh , Jason R. Marden

In iterated games, a player can unilaterally exert influence over the outcome through a careful choice of strategy. A powerful class of such "payoff control" strategies was discovered by Press and Dyson (2012). Their so-called…

Computer Science and Game Theory · Computer Science 2022-07-07 Arjun Mirani , Alex McAvoy

This work lies in the fusion of experimental economics and data mining. It continues author's previous work on mining behaviour rules of human subjects from experimental data, where game-theoretic predictions partially fail to work.…

Computer Science and Game Theory · Computer Science 2012-11-13 Rustam Tagiew