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We describe an efficient algorithm to compute solutions for the general two-player Blotto game on n battlefields with heterogeneous values. While explicit constructions for such solutions have been limited to specific, largely symmetric or…

Computer Science and Game Theory · Computer Science 2022-06-01 Vianney Perchet , Philippe Rigollet , Thibaut Le Gouic

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

Zero-sum stochastic games are easy to solve as they can be cast as simple Markov decision processes. This is however not the case with general-sum stochastic games. A fairly general optimization problem formulation is available for…

Machine Learning · Computer Science 2015-07-02 H. L. Prasad , Shalabh Bhatnagar

We consider a sub-class of bi-matrix games which we refer to as two-person (hereafter referred to as two-player) additively-separable sum (TPASS) games, where the sum of the pay-offs of the two players is additively separable. The row…

Optimization and Control · Mathematics 2025-11-03 Somdeb Lahiri

We investigate the computation of equilibria in extensive-form games where ex ante correlation is possible, focusing on correlated equilibria requiring the least amount of communication between the players and the mediator. Motivated by the…

Computer Science and Game Theory · Computer Science 2019-01-21 Andrea Celli , Stefano Coniglio , Nicola Gatti

We study the problem of finding optimal correlated equilibria of various sorts in extensive-form games: normal-form coarse correlated equilibrium (NFCCE), extensive-form coarse correlated equilibrium (EFCCE), and extensive-form correlated…

Computer Science and Game Theory · Computer Science 2025-01-28 Brian Zhang , Gabriele Farina , Andrea Celli , Tuomas Sandholm

Motivated by applications to data networks where fast convergence is essential, we analyze the problem of learning in generic N-person games that admit a Nash equilibrium in pure strategies. Specifically, we consider a scenario where…

Computer Science and Game Theory · Computer Science 2016-08-01 Johanne Cohen , Amélie Héliou , Panayotis Mertikopoulos

In security games, the solution concept commonly used is that of a Stackelberg equilibrium where the defender gets to commit to a mixed strategy. The motivation for this is that the attacker can repeatedly observe the defender's actions and…

Computer Science and Game Theory · Computer Science 2016-10-17 Vincent Conitzer

In this work we present a hierarchical framework for solving discrete stochastic pursuit-evasion games (PEGs) in large grid worlds. With a partition of the grid world into superstates (e.g., "rooms"), the proposed approach creates a…

Multiagent Systems · Computer Science 2023-03-20 Yue Guan , Mohammad Afshari , Qifan Zhang , Panagiotis Tsiotras

We analyse the computational complexity of finding Nash equilibria in stochastic multiplayer games with $\omega$-regular objectives. While the existence of an equilibrium whose payoff falls into a certain interval may be undecidable, we…

Computer Science and Game Theory · Computer Science 2010-06-24 Michael Ummels , Dominik Wojtczak

We derive sublinear-time quantum algorithms for computing the Nash equilibrium of two-player zero-sum games, based on efficient Gibbs sampling methods. We are able to achieve speed-ups for both dense and sparse payoff matrices at the cost…

Quantum Physics · Physics 2019-04-08 Joran van Apeldoorn , András Gilyén

Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of agents, for example labeling them `winner' and `loser'. If the game is approximately transitive, then self-play generates sequences of agents of…

Machine Learning · Computer Science 2019-05-14 David Balduzzi , Marta Garnelo , Yoram Bachrach , Wojciech M. Czarnecki , Julien Perolat , Max Jaderberg , Thore Graepel

Successful algorithms have been developed for computing Nash equilibrium in a variety of finite game classes. However, solving continuous games -- in which the pure strategy space is (potentially uncountably) infinite -- is far more…

Computer Science and Game Theory · Computer Science 2021-06-02 Sam Ganzfried

This paper considers the problem of inverse reinforcement learning in zero-sum stochastic games when expert demonstrations are known to be not optimal. Compared to previous works that decouple agents in the game by assuming optimality in…

Machine Learning · Statistics 2018-06-07 Xingyu Wang , Diego Klabjan

Many real-world domains contain multiple agents behaving strategically with probabilistic transitions and uncertain (potentially infinite) duration. Such settings can be modeled as stochastic games. While algorithms have been developed for…

Computer Science and Game Theory · Computer Science 2020-06-25 Sam Ganzfried , Conner Laughlin , Charles Morefield

We study the computational complexity of finding Stackelberg Equilibria in general-sum games, where the set of pure strategies of the leader and the followers are exponentially large in a natrual representation of the problem. In…

Computer Science and Game Theory · Computer Science 2019-09-10 Avrim Blum , Nika Hagtalab , MohammadTaghi Hajiaghayi , Saeed Seddighin

We study equilibrium computation with extensive-form correlation in two-player turn-taking stochastic games. Our main results are two-fold: (1) We give an algorithm for computing a Stackelberg extensive-form correlated equilibrium (SEFCE),…

Computer Science and Game Theory · Computer Science 2024-12-24 Hanrui Zhang , Yu Cheng , Vincent Conitzer

We study the computation of equilibria of anonymous games, via algorithms that may proceed via a sequence of adaptive queries to the game's payoff function, assumed to be unknown initially. The general topic we consider is \emph{query…

Computer Science and Game Theory · Computer Science 2016-05-06 Paul W. Goldberg , Stefano Turchetta

While Nash equilibrium in extensive-form games is well understood, very little is known about the properties of extensive-form correlated equilibrium (EFCE), both from a behavioral and from a computational point of view. In this setting,…

Computer Science and Game Theory · Computer Science 2019-10-29 Gabriele Farina , Chun Kai Ling , Fei Fang , Tuomas Sandholm

The complexity of computing equilibrium refinements has been at the forefront of algorithmic game theory research, but it has remained open in the seminal class of potential games; we close this fundamental gap in this paper. We first show…

Computer Science and Game Theory · Computer Science 2026-02-11 Ioannis Anagnostides , Maria-Florina Balcan , Kiriaki Fragkia , Tuomas Sandholm , Emanuel Tewolde , Brian Hu Zhang