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In this paper, we introduce an agent-based representation of games, in order to propose a compact representation for multi-party games in game theory. Our method is inspired by concepts in process theory and process algebra. In addition, we…

Computer Science and Game Theory · Computer Science 2021-10-28 Omid Gheibi , Rasoul Ramezanian

Solvency games, introduced by Berger et al., provide an abstract framework for modelling decisions of a risk-averse investor, whose goal is to avoid ever going broke. We study a new variant of this model, where, in addition to stochastic…

Computational Engineering, Finance, and Science · Computer Science 2013-10-14 Tomáš Brázdil , Taolue Chen , Vojtěch Forejt , Petr Novotný , Aistis Simaitis

The article provides a solution algorithm for the linear programming problem (LPP) with the latter being presented as an antagonistic matrix game so the game's further solution is based on the iterative method. The algorithm is presented as…

Optimization and Control · Mathematics 2019-05-15 Vilisov V. Ya

In this paper, we settle the sampling complexity of solving discounted two-player turn-based zero-sum stochastic games up to polylogarithmic factors. Given a stochastic game with discount factor $\gamma\in(0,1)$ we provide an algorithm that…

Machine Learning · Computer Science 2019-08-30 Aaron Sidford , Mengdi Wang , Lin F. Yang , Yinyu Ye

Infinitely repeated games support equilibrium concepts beyond those present in one-shot games (e.g., cooperation in the prisoner's dilemma). Nonetheless, repeated games fail to capture our real-world intuition for settings with many…

Computer Science and Game Theory · Computer Science 2025-05-22 Henry Fleischmann , Kiriaki Fragkia , Ratip Emin Berker

Optimization under uncertainty is a fundamental problem in learning and decision-making, particularly in multi-agent systems. Previously, Feldman, Kalai, and Tennenholtz [2010] demonstrated the ability to efficiently compete in repeated…

Computer Science and Game Theory · Computer Science 2026-01-29 Daniel Ablin , Alon Cohen

Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackle this problem, we develop a unified framework for reward function recovery in two-player…

Machine Learning · Computer Science 2026-05-20 Junyi Liao , Zihan Zhu , Ethan Fang , Zhuoran Yang , Vahid Tarokh

Negotiations, a model of concurrency with multi party negotiation as primitive, have been recently introduced by J. Desel and J. Esparza. We initiate the study of games for this model. We study coalition problems: can a given coalition of…

Logic in Computer Science · Computer Science 2015-09-25 Philipp Hoffmann

We give an algorithm for solving stochastic parity games with almost-sure winning conditions on lossy channel systems, for the case where the players are restricted to finite-memory strategies. First, we describe a general framework, where…

Computer Science and Game Theory · Computer Science 2013-06-14 Parosh Aziz Abdulla , Lorenzo Clemente , Richard Mayr , Sven Sandberg

Games on graphs provide a natural model for reactive non-terminating systems. In such games, the interaction of two players on an arena results in an infinite path that describes a run of the system. Different settings are used to model…

Computer Science and Game Theory · Computer Science 2011-06-08 Krishnendu Chatterjee , Nathanaël Fijalkow

A new class of multi-player competitive stochastic games in discrete-time with an affine specification of the redistribution of payoffs at exercise is proposed and examined. Our games cover as a very special case the classic two-person…

Probability · Mathematics 2014-05-13 Ivan Guo , Marek Rutkowski

Nonzero-sum stochastic differential games with impulse controls offer a realistic and far-reaching modelling framework for applications within finance, energy markets, and other areas, but the difficulty in solving such problems has…

Numerical Analysis · Mathematics 2020-06-29 Diego Zabaljauregui

Strategy iteration is a technique frequently used for two-player games in order to determine the winner or compute payoffs, but to the best of our knowledge no general framework for strategy iteration has been considered. Inspired by…

Logic in Computer Science · Computer Science 2022-12-14 Paolo Baldan , Richard Eggert , Barbara König , Tommaso Padoan

We consider an N-player hierarchical game in which the i-th player's objective comprises of an expectation-valued term, parametrized by rival decisions, and a hierarchical term. Such a framework allows for capturing a broad range of…

Optimization and Control · Mathematics 2024-01-26 Shisheng Cui , Uday V. Shanbhag , Mathias Staudigl

This paper provides a new version of matrix semi-tensor product method based on adjacent transpositions to test symmetric games. The advantage of using adjacent transpositions lies in the great simplification of analysis of symmetric games.…

Computer Science and Game Theory · Computer Science 2022-02-22 Lei Wang , Xinyun Liu , Ting Li , Jiandong Zhu

Matching games is a one-to-one two sided market model introduced by Garrido-Lucero and Laraki, in which coupled agents' utilities are endogenously determined as the outcome of a strategic game. They refine the classical pairwise stability…

Computer Science and Game Theory · Computer Science 2025-07-22 Felipe Garrido-Lucero , Rida Laraki

Parity games are abstract infinite-round games that take an important role in formal verification. In the basic setting, these games are two-player, turn-based, and played under perfect information on directed graphs, whose nodes are…

Computer Science and Game Theory · Computer Science 2019-10-31 Antonio Di Stasio , Aniello Murano , Giuseppe Perelli , Moshe Y. Vardi

In this article, we introduce a new class of entropy-penalized robust mean field game problems in which the representative agent is opposed to Nature. The agent's objective is formulated as a min-max stochastic control problem, in which…

Optimization and Control · Mathematics 2026-03-27 François Delarue , Pierre Lavigne

Simple stochastic games are two-player zero-sum stochastic games with turn-based moves, perfect information, and reachability winning conditions. We present two new algorithms computing the values of simple stochastic games. Both of them…

Computer Science and Game Theory · Computer Science 2015-07-01 Hugo Gimbert , Florian Horn

Economic ensembles can be modeled as networks of interacting agents whose be-haviors are described in terms of game theory. The evolutionary paradigm has been applied to two-person games to discover strategies in this context.…

Condensed Matter · Physics 2007-05-23 Wan Ahmad Tajuddin Wan Abdullah