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Feature-based SPL analysis and family-based model checking have seen rapid development. Many model checking problems can be reduced to two-player games on finite graphs. A prominent example is mu-calculus model checking, which is generally…

Logic in Computer Science · Computer Science 2020-05-15 Uli Fahrenberg , Axel Legay

Although mixed extensions of finite games always admit equilibria, this is not the case for countable games, the best-known example being Wald's pick-the-larger-integer game. Several authors have provided conditions for the existence of…

Computer Science and Game Theory · Computer Science 2017-04-04 Valerio Capraro , Marco Scarsini

We study two-player concurrent stochastic games on finite graphs, with B\"uchi and co-B\"uchi objectives. The goal of the first player is to maximize the probability of satisfying the given objective. Following Martin's determinacy theorem…

Computer Science and Game Theory · Computer Science 2022-11-28 Benjamin Bordais , Patricia Bouyer , Stéphane Le Roux

We explain a highly efficient algorithm for playing the simplest type of dots and boxes endgame optimally (by which we mean "in such a way so as to maximise the number of boxes that you take"). The algorithm is sufficiently simple that it…

Combinatorics · Mathematics 2014-05-19 Kevin Buzzard , Michael Ciere

In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. A cluster groups together agents with a similar "strategic…

Computer Science and Game Theory · Computer Science 2012-06-18 Sevan G. Ficici , David C. Parkes , Avi Pfeffer

It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is particularly pronounced for computationally hard problems,…

Machine Learning · Computer Science 2018-11-29 Pascal Kerschke , Holger H. Hoos , Frank Neumann , Heike Trautmann

We consider differentiable games where the goal is to find a Nash equilibrium. The machine learning community has recently started using variants of the gradient method (GD). Prime examples are extragradient (EG), the optimistic gradient…

Machine Learning · Computer Science 2020-07-08 Waïss Azizian , Ioannis Mitliagkas , Simon Lacoste-Julien , Gauthier Gidel

Coalitions naturally exist in many real-world systems involving multiple decision makers such as ridesharing, security, and online ad auctions, but the coalition structure among the agents is often unknown. We propose and study an important…

Computer Science and Game Theory · Computer Science 2023-12-20 Yixuan Even Xu , Chun Kai Ling , Fei Fang

We show the existence and effective computability of optimal winning strategies for request-response games in case the quality of a play is measured by the limit superior of the mean accumulated waiting times between requests and their…

Formal Languages and Automata Theory · Computer Science 2014-06-19 Florian Horn , Wolfgang Thomas , Nico Wallmeier , Martin Zimmermann

Partial monitoring is an expressive framework for sequential decision-making with an abundance of applications, including graph-structured and dueling bandits, dynamic pricing and transductive feedback models. We survey and extend recent…

Machine Learning · Computer Science 2023-11-15 Johannes Kirschner , Tor Lattimore , Andreas Krause

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

We study Stackelberg equilibria in finitely repeated games, where the leader commits to a strategy that picks actions in each round and can be adaptive to the history of play (i.e. they commit to an algorithm). In particular, we study…

Computer Science and Game Theory · Computer Science 2024-03-08 Natalie Collina , Eshwar Ram Arunachaleswaran , Michael Kearns

This paper uses category theory to develop an entirely new approach to approximate game theory. Game theory is the study of how different agents within a multi-agent system take decisions. At its core, game theory asks what an optimal…

Computer Science and Game Theory · Computer Science 2025-09-26 Neil Ghani

We study the real-valued combinatorial pure exploration of the multi-armed bandit (R-CPE-MAB) problem. In R-CPE-MAB, a player is given $d$ stochastic arms, and the reward of each arm $s\in\{1, \ldots, d\}$ follows an unknown distribution…

Machine Learning · Computer Science 2023-11-16 Shintaro Nakamura , Masashi Sugiyama

In a reachability-time game, players Min and Max choose moves so that the time to reach a final state in a timed automaton is minimised or maximised, respectively. Asarin and Maler showed decidability of reachability-time games on strongly…

Computational Complexity · Computer Science 2020-01-16 Marcin Jurdziński , Ashutosh Trivedi

We formulate the novel class of contextual games, a type of repeated games driven by contextual information at each round. By means of kernel-based regularity assumptions, we model the correlation between different contexts and game…

Computer Science and Game Theory · Computer Science 2021-07-15 Pier Giuseppe Sessa , Ilija Bogunovic , Andreas Krause , Maryam Kamgarpour

We show that the Brier game of prediction is mixable and find the optimal learning rate and substitution function for it. The resulting prediction algorithm is applied to predict results of football and tennis matches. The theoretical…

Machine Learning · Computer Science 2009-11-02 Vladimir Vovk , Fedor Zhdanov

From the very dawn of the field, search with value functions was a fundamental concept of computer games research. Turing's chess algorithm from 1950 was able to think two moves ahead, and Shannon's work on chess from $1950$ includes an…

Artificial Intelligence · Computer Science 2021-11-12 Martin Schmid

This paper studies the mechanisms, implications, and potential applications of the recently discovered class of Zero Determinant (ZD) strategies in iterated 2x2 games. These strategies were reported to successfully extort pure economic…

Computer Science and Game Theory · Computer Science 2013-08-13 Lars Roemheld

Modern reinforcement learning systems produce many high-quality policies throughout the learning process. However, to choose which policy to actually deploy in the real world, they must be tested under an intractable number of environmental…

Machine Learning · Computer Science 2023-06-14 Dustin Morrill , Thomas J. Walsh , Daniel Hernandez , Peter R. Wurman , Peter Stone
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