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We examine online safe multi-agent reinforcement learning using constrained Markov games in which agents compete by maximizing their expected total rewards under a constraint on expected total utilities. Our focus is confined to an episodic…

Machine Learning · Computer Science 2023-06-02 Dongsheng Ding , Xiaohan Wei , Zhuoran Yang , Zhaoran Wang , Mihailo R. Jovanović

The convexification numerical method with the rigorously established global convergence property is constructed for a problem for the Mean Field Games System of the second order. This is the problem of the retrospective analysis of a game…

Numerical Analysis · Mathematics 2023-06-30 Michael V. Klibanov , Jingzhi Li , Zhipeng Yang

The equivalence between von Neumann's Minimax Theorem for zero-sum games and the LP Duality Theorem connects cornerstone problems of the two fields of game theory and optimization, respectively, and has been the subject of intense scrutiny…

Computer Science and Game Theory · Computer Science 2026-01-30 Ilan Adler , Martin Bullinger , Vijay V. Vazirani

Zero-sum asymmetric games model decision making scenarios involving two competing players who have different information about the game being played. A particular case is that of nested information, where one (informed) player has superior…

Computer Science and Game Theory · Computer Science 2017-11-08 Lichun Li , Jeff S. Shamma

Muller games are played by two players moving a token along a graph; the winner is determined by the set of vertices that occur infinitely often. The central algorithmic problem is to compute the winning regions for the players. Different…

Logic in Computer Science · Computer Science 2013-07-24 A. Grinshpun , P. Phalitnonkiat , S. Rubin , A. Tarfulea

This paper studies approximate solutions to large-scale linear quadratic stochastic games with homogeneous nodal dynamics parameters and heterogeneous network couplings within the graphon mean field game framework in [2]-[4]. A graphon…

Systems and Control · Electrical Eng. & Systems 2021-10-22 Shuang Gao , Peter E. Caines , Minyi Huang

We consider the problem of learning to play a repeated multi-agent game with an unknown reward function. Single player online learning algorithms attain strong regret bounds when provided with full information feedback, which unfortunately…

Machine Learning · Computer Science 2019-10-29 Pier Giuseppe Sessa , Ilija Bogunovic , Maryam Kamgarpour , Andreas Krause

We propose a unifying additive theory for standard conventions in Combinatorial Game Theory, including normal-, mis\`ere- and scoring-play, studied by Berlekamp, Conway, Dorbec, Ettinger, Guy, Larsson, Milley, Neto, Nowakowski, Renault,…

Combinatorics · Mathematics 2021-07-07 Urban Larsson , Richard J. Nowakowski , Carlos P. Santos

While fictitious play is guaranteed to converge to Nash equilibrium in certain game classes, such as two-player zero-sum games, it is not guaranteed to converge in non-zero-sum and multiplayer games. We show that fictitious play in fact…

Computer Science and Game Theory · Computer Science 2024-07-30 Sam Ganzfried

We consider two-player games over finite graphs in which both players are restricted by fairness constraints on their moves. Given a two player game graph $G=(V,E)$ and a set of fair moves $E_f\subseteq E$ a player is said to play "fair" in…

Computer Science and Game Theory · Computer Science 2026-05-12 Daniel Hausmann , Nir Piterman , Irmak Sağlam , Anne-Kathrin Schmuck

Simple stochastic games can be solved by value iteration (VI), which yields a sequence of under-approximations of the value of the game. This sequence is guaranteed to converge to the value only in the limit. Since no stopping criterion is…

Logic in Computer Science · Computer Science 2021-02-02 Edon Kelmendi , Julia Krämer , Jan Kretinsky , Maximilian Weininger

Evolutionary game theory is a powerful mathematical framework to study how intelligent individuals adjust their strategies in collective interactions. It has been widely believed that it is impossible to unilaterally control players'…

Optimization and Control · Mathematics 2021-08-31 Renfei Tan , Qi Su , Bin Wu , Long Wang

We consider concurrent games played on graphs. At every round of the game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety…

Computer Science and Game Theory · Computer Science 2008-12-18 Krishnendu Chatterjee , Luca de Alfaro , Thomas A. Henzinger

In this paper we study two-player bilinear zero-sum games with constrained strategy spaces. An instance of natural occurrences of such constraints is when mixed strategies are used, which correspond to a probability simplex constraint. We…

Computer Science and Game Theory · Computer Science 2022-06-10 Andre Wibisono , Molei Tao , Georgios Piliouras

In a mean-payoff parity game, one of the two players aims both to achieve a qualitative parity objective and to minimize a quantitative long-term average of payoffs (aka. mean payoff). The game is zero-sum and hence the aim of the other…

Computer Science and Game Theory · Computer Science 2020-01-15 Laure Daviaud , Marcin Jurdzinski , Ranko Lazic

This paper presents a new lower bound for the discrete strategy improvement algorithm for solving parity games due to Voege and Jurdziski. First, we informally show which structures are difficult to solve for the algorithm. Second, we…

Computer Science and Game Theory · Computer Science 2009-01-20 Oliver Friedmann

In this work, we show that parallel repetition of public-coin interactive arguments reduces the soundness error at an exponential rate even in the post-quantum setting. Moreover, we generalize this result to hold for threshold verifiers,…

Quantum Physics · Physics 2025-06-17 Andrew Huang , Yael Tauman Kalai

Fictitious Play (FP) is a simple and natural dynamic for repeated play in zero-sum games. Proposed by Brown in 1949, FP was shown to converge to a Nash Equilibrium by Robinson in 1951, albeit at a slow rate that may depend on the dimension…

Computer Science and Game Theory · Computer Science 2020-11-17 Jacob Abernethy , Kevin A. Lai , Andre Wibisono

Matrix diagonalization is at the cornerstone of numerous fields of scientific computing. Diagonalizing a matrix to solve an eigenvalue problem requires a sequential path of iterations that eventually reaches a sufficiently converged and…

We study tensor norms over Banach spaces and their relations to quantum information theory, in particular their connection with two-prover games. We consider a version of the Hilbertian tensor norm $\gamma_2$ and its dual $\gamma_2^*$ that…

Quantum Physics · Physics 2011-05-04 Dejan D. Dukaric
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