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Matching games is a novel matching model introduced by Garrido-Lucero and Laraki, in which agents' utilities are endogenously determined as the outcome of a strategic game they play simultaneously with the matching process. Matching games…

Computer Science and Game Theory · Computer Science 2025-07-23 Felipe Garrido-Lucero , Rida Laraki

An improved translation from alternating parity automata on infinite words to alternating weak automata is given. The blow-up of the number of states is related to the size of the smallest universal ordered trees and hence it is…

Formal Languages and Automata Theory · Computer Science 2020-01-15 Laure Daviaud , Marcin Jurdziński , Karoliina Lehtinen

In this thesis, we settle the computational complexity of some fundamental questions in polynomial optimization. These include the questions of (i) finding a local minimum, (ii) testing local minimality of a point, and (iii) deciding…

Optimization and Control · Mathematics 2020-08-28 Jeffrey Zhang

Infinitely repeated games can support cooperative outcomes that are not equilibria in the one-shot game. The idea is to make sure that any gains from deviating will be offset by retaliation in future rounds. However, this model of…

Computer Science and Game Theory · Computer Science 2024-06-04 Ratip Emin Berker , Vincent Conitzer

Policy-based methods with function approximation are widely used for solving two-player zero-sum games with large state and/or action spaces. However, it remains elusive how to obtain optimization and statistical guarantees for such…

Machine Learning · Computer Science 2022-03-01 Yulai Zhao , Yuandong Tian , Jason D. Lee , Simon S. Du

We develop a quasi-polynomial time Las Vegas algorithm for approximating Nash equilibria in polymatrix games over trees, under a mild renormalizing assumption. Our result, in particular, leads to an expected polynomial-time algorithm for…

Computer Science and Game Theory · Computer Science 2016-04-12 Siddharth Barman , Katrina Ligett , Georgios Piliouras

Convergence of the policy iteration method for discrete and continuous optimal control problems holds under general assumptions. Moreover, in some circumstances, it is also possible to show a quadratic rate of convergence for the algorithm.…

Optimization and Control · Mathematics 2022-03-02 Fabio Camilli , Qing Tang

Self-play, where the algorithm learns by playing against itself without requiring any direct supervision, has become the new weapon in modern Reinforcement Learning (RL) for achieving superhuman performance in practice. However, the…

Machine Learning · Computer Science 2020-07-10 Yu Bai , Chi Jin

We show how to construct sparse polynomial systems that have non-trivial lower bounds on their numbers of real solutions. These are unmixed systems associated to certain polytopes. For the order polytope of a poset P this lower bound is the…

Algebraic Geometry · Mathematics 2010-03-29 Evgenia Soprunova , Frank Sottile

We consider concurrent stochastic games played on graphs with reachability and safety objectives. These games can be solved by value iteration as well as strategy iteration, each of them yielding a sequence of under-approximations of the…

Computer Science and Game Theory · Computer Science 2019-09-19 Julia Eisentraut , Jan Křetínský , Alexej Rotar

In this paper, we study games with continuous action spaces and non-linear payoff functions. Our key insight is that Lipschitz continuity of the payoff function allows us to provide algorithms for finding approximate equilibria in these…

Computer Science and Game Theory · Computer Science 2016-03-31 Argyrios Deligkas , John Fearnley , Paul Spirakis

We investigate the interrelation between graph searching games and games with imperfect information. As key consequence we obtain that parity games with bounded imperfect information can be solved in PTIME on graphs of bounded DAG-width…

Computer Science and Game Theory · Computer Science 2015-03-19 Bernd Puchala , Roman Rabinovich

We study the iteration complexity of decentralized learning of approximate correlated equilibria in incomplete information games. On the negative side, we prove that in $\mathit{extensive}$-$\mathit{form}$ $\mathit{games}$, assuming…

Computer Science and Game Theory · Computer Science 2024-06-05 Binghui Peng , Aviad Rubinstein

Stochastic games are a classical model in game theory in which two opponents interact and the environment changes in response to the players' behavior. The central solution concepts for these games are the discounted values and the value,…

Optimization and Control · Mathematics 2019-12-12 Miquel Oliu-Barton

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

We revisit the problem of finding optimal strategies for deterministic Markov Decision Processes (DMDPs), and a closely related problem of testing feasibility of systems of $m$ linear inequalities on $n$ real variables with at most two…

Data Structures and Algorithms · Computer Science 2021-10-29 Adam Karczmarz

The 3-domatic number problem asks whether a given graph can be partitioned intothree dominating sets. We prove that this problem can be solved by a deterministic algorithm in time 2.695^n (up to polynomial factors). This result improves the…

Computational Complexity · Computer Science 2007-05-23 Tobias Riege , Jörg Rothe , Holger Spakowski , Masaki Yamamoto

Iterated coopetitive games capture the situation when one must efficiently balance between cooperation and competition with the other agents over time in order to win the game (e.g., to become the player with highest total utility).…

Computer Science and Game Theory · Computer Science 2022-03-11 Shivakumar Mahesh , Nicholas Bishop , Le Cong Dinh , Long Tran-Thanh

We investigate sublinear classical and quantum algorithms for matrix games, a fundamental problem in optimization and machine learning, with provable guarantees. Given a matrix $A\in\mathbb{R}^{n\times d}$, sublinear algorithms for the…

Quantum Physics · Physics 2020-12-14 Tongyang Li , Chunhao Wang , Shouvanik Chakrabarti , Xiaodi Wu

We study the complexity of computing equilibria in two classes of network games based on flows - fractional BGP (Border Gateway Protocol) games and fractional BBC (Bounded Budget Connection) games. BGP is the glue that holds the Internet…

Computer Science and Game Theory · Computer Science 2008-12-05 Laura J. Poplawski , Rajmohan Rajaraman , Ravi Sundaram , Shang-Hua Teng