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Poker is a large complex game of imperfect information, which has been singled out as a major AI challenge problem. Recently there has been a series of breakthroughs culminating in agents that have successfully defeated the strongest human…

Artificial Intelligence · Computer Science 2022-06-28 Sam Ganzfried , Max Chiswick

We propose a distributed algorithm to compute an equilibrium in aggregate games where players communicate over a fixed undirected network. Our algorithm exploits correlated perturbation to obfuscate information shared over the network. We…

Optimization and Control · Mathematics 2019-12-16 Shripad Gade , Anna Winnicki , Subhonmesh Bose

The peculiarity of adversarial team games resides in the asymmetric information available to the team members during the play, which makes the equilibrium computation problem hard even with zero-sum payoffs. The algorithms available in the…

Computer Science and Game Theory · Computer Science 2022-01-26 Luca Carminati , Federico Cacciamani , Marco Ciccone , Nicola Gatti

Strategic agents in incomplete-information environments have a conflicted relationship with uncertainty: it can keep them unpredictable to their opponents, but it must also be overcome to predict the actions of those opponents. We use a…

Computer Science and Game Theory · Computer Science 2016-05-16 Seth Frey , Paul L. Williams , Dominic K. Albino

Real-life agents seldom have unlimited reasoning power. In this paper, we propose and study a new formal notion of computationally bounded strategic ability in multi-agent systems. The notion characterizes the ability of a set of agents to…

Multiagent Systems · Computer Science 2023-10-27 Catalin Dima , Wojciech Jamroga

There has been a recent surge of interest in the role of information in strategic interactions. Much of this work seeks to understand how the realized equilibrium of a game is influenced by uncertainty in the environment and the information…

Computer Science and Game Theory · Computer Science 2014-07-22 Shaddin Dughmi

Usually, to apply game-theoretic methods, we must specify utilities precisely, and we run the risk that the solutions we compute are not robust to errors in this specification. Ordinal games provide an attractive alternative: they require…

Computer Science and Game Theory · Computer Science 2024-07-11 Vincent Conitzer

Poker is ideal for testing automated reasoning under uncertainty. It introduces uncertainty both by physical randomization and by incomplete information about opponents hands.Another source OF uncertainty IS the limited information…

Artificial Intelligence · Computer Science 2013-01-30 Kevin B. Korb , Ann Nicholson , Nathalie Jitnah

Understanding how people behave in strategic settings--where they make decisions based on their expectations about the behavior of others--is a long-standing problem in the behavioral sciences. We conduct the largest study to date of…

General Economics · Economics 2024-08-16 Jian-Qiao Zhu , Joshua C. Peterson , Benjamin Enke , Thomas L. Griffiths

We develop a new approach that computes approximate equilibrium strategies in Jotto, a popular word game. Jotto is an extremely large two-player game of imperfect information; its game tree has many orders of magnitude more states than…

Computer Science and Game Theory · Computer Science 2016-03-15 Sam Ganzfried

While we would like agents that can coordinate with humans, current algorithms such as self-play and population-based training create agents that can coordinate with themselves. Agents that assume their partner to be optimal or similar to…

Machine Learning · Computer Science 2020-01-10 Micah Carroll , Rohin Shah , Mark K. Ho , Thomas L. Griffiths , Sanjit A. Seshia , Pieter Abbeel , Anca Dragan

We introduce a class of extensive form games where players might not be able to foresee the possible consequences of their decisions and form a model of their opponents which they exploit to achieve a more profitable outcome. We improve…

Artificial Intelligence · Computer Science 2016-05-31 Paolo Turrini

We consider the problem of predicting human players' actions in repeated strategic interactions. Our goal is to predict the dynamic step-by-step behavior of individual players in previously unseen games. We study the ability of neural…

Computer Science and Game Theory · Computer Science 2019-11-11 Yoav Kolumbus , Gali Noti

Game theoretic equilibria are mathematical expressions of rationality. Rational agents are used to model not only humans and their software representatives, but also organisms, populations, species and genes, interacting with each other and…

Computer Science and Game Theory · Computer Science 2015-05-13 Dusko Pavlovic

Poker is a family of card games that includes many variations. We hypothesize that most poker games can be solved as a pattern matching problem, and propose creating a strong poker playing system based on a unified poker representation. Our…

Artificial Intelligence · Computer Science 2015-09-23 Nikolai Yakovenko , Liangliang Cao , Colin Raffel , James Fan

If humans understood language by randomly selecting parsing actions, it might have been necessary to construct a robust symbolic system capable of being interpreted under any hierarchical structure. However, human parsing strategies do not…

Computation and Language · Computer Science 2025-06-30 Daichi Kato , Ryo Ueda , Yusuke Miyao

In online advertising, search engines sell ad placements for keywords continuously through auctions. This problem can be seen as an infinitely repeated game since the auction is executed whenever a user performs a query with the keyword. As…

Computer Science and Game Theory · Computer Science 2022-01-25 Francesco Belardinelli , Wojtek Jamroga , Vadim Malvone , Munyque Mittelmann , Aniello Murano , Laurent Perrussel

Poker is in the family of imperfect information games unlike other games such as chess, connect four, etc which are perfect information game instead. While many perfect information games have been solved, no non-trivial imperfect…

Computer Science and Game Theory · Computer Science 2024-01-15 Prathamesh Sonawane , Arav Chheda

Many studies have shown that humans are "predictably irrational": they do not act in a fully rational way, but their deviations from rational behavior are quite systematic. Our goal is to see the extent to which we can explain and justify…

Computer Science and Game Theory · Computer Science 2023-07-27 Xinming Liu , Joseph Y. Halpern

Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products,…

Computer Science and Game Theory · Computer Science 2019-05-09 Omer Ben-Porat , Moshe Tennenholtz
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