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We introduce and analyze a natural game formulated as follows. In this one-person game, the player is given a random permutation $A=(a_1,\dots, a_n)$ of a multiset $M$ of $n$ reals that sum up to $0$, where each of the $n!$ permutation…

Discrete Mathematics · Computer Science 2024-11-21 Adrian Dumitrescu , Arsenii Sagdeev

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

Consider a two-player zero-sum stochastic game where the transition function can be embedded in a given feature space. We propose a two-player Q-learning algorithm for approximating the Nash equilibrium strategy via sampling. The algorithm…

Machine Learning · Computer Science 2019-06-04 Zeyu Jia , Lin F. Yang , Mengdi Wang

We present a novel framework for {\epsilon}-optimally solving two-player zero-sum partially observable stochastic games (zs-POSGs). These games pose a major challenge due to the absence of a principled connection with dynamic programming…

Computer Science and Game Theory · Computer Science 2025-11-17 Erwan Christian Escudie , Matthia Sabatelli , Olivier Buffet , Jilles Steeve Dibangoye

When looking for a solution, deterministic methods have the enormous advantage that they do find global optima. Unfortunately, they are very CPU-intensive, and are useless on untractable NP-hard problems that would require thousands of…

Neural and Evolutionary Computing · Computer Science 2011-12-20 Pierre Collet , Jean-Philippe Rennard

We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of Riemannian optimization, game theory and optimal transport,…

Optimization and Control · Mathematics 2022-12-29 Mohammad Reza Karimi , Ya-Ping Hsieh , Panayotis Mertikopoulos , Andreas Krause

An important challenge in non-cooperative game theory is coordinating on a single (approximate) equilibrium from many possibilities - a challenge that becomes even more complex when players hold private information. Recommender mechanisms…

Computer Science and Game Theory · Computer Science 2025-05-30 Bengisu Guresti , Chongjie Zhang , Yevgeniy Vorobeychik

We present a deterministic algorithm, solving discounted games with $n$ nodes in $n^{O(1)}\cdot (2 + \sqrt{2})^n$-time. For bipartite discounted games our algorithm runs in $n^{O(1)}\cdot 2^n$-time. Prior to our work no deterministic…

Data Structures and Algorithms · Computer Science 2020-10-27 Alexander Kozachinskiy

The semi-random graph process is a single player game in which the player is initially presented an empty graph on $n$ vertices. In each round, a vertex $u$ is presented to the player independently and uniformly at random. The player then…

Combinatorics · Mathematics 2023-07-11 Paweł Prałat , Harjas Singh

This paper introduces a novel algorithm for two-player deterministic games with perfect information, which we call PROBS (Predict Results of Beam Search). Unlike existing methods that predominantly rely on Monte Carlo Tree Search (MCTS) for…

Artificial Intelligence · Computer Science 2024-04-26 Sergey Pastukhov

The success of adversarial formulations in machine learning has brought renewed motivation for smooth games. In this work, we focus on the class of stochastic Hamiltonian methods and provide the first convergence guarantees for certain…

A zero-sum two-person Perfect Information Semi-Markov game (PISMG) under limiting ratio average payoff has a value and both the maximiser and the minimiser have optimal pure semi-stationary strategies. We arrive at the result by first…

Computer Science and Game Theory · Computer Science 2023-02-15 S. Sinha , K. G. Bakshi

We study observation-based strategies for two-player turn-based games on graphs with omega-regular objectives. An observation-based strategy relies on imperfect information about the history of a play, namely, on the past sequence of…

Logic in Computer Science · Computer Science 2015-07-01 Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger , <br> Jean-Francois Raskin

Probabilistic timed automata are a suitable formalism to model systems with real-time, nondeterministic and probabilistic behaviour. We study two-player zero-sum games on such automata where the objective of the game is specified as the…

Logic in Computer Science · Computer Science 2016-04-18 Vojtěch Forejt , Marta Kwiatkowska , Gethin Norman , Ashutosh Trivedi

We consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph $G = (V, E)$, with local rewards $r: E \to \ZZ$, and three types of positions: black $V_B$, white $V_W$, and random…

Data Structures and Algorithms · Computer Science 2016-10-24 Endre Boros , Khaled Elbassioni , Vladimir Gurvich , Kazuhisa Makino

This thesis presents some geometric insights into three different types of two player prediction games -- namely general learning task, prediction with expert advice, and online convex optimization. These games differ in the nature of the…

Machine Learning · Computer Science 2018-05-23 Parameswaran Kamalaruban

We study a class of two-player zero-sum stochastic games known as \textit{blind stochastic games}, where players neither observe the state nor receive any information about it during the game. A central concept for analyzing long-duration…

Optimization and Control · Mathematics 2025-11-24 Krishnendu Chatterjee , David Lurie , Raimundo Saona , Bruno Ziliotto

The multiplication game is a two-person game in which each player chooses a positive integer without knowledge of the other player's number. The two numbers are then multiplied together and the first digit of the product determines the…

Computer Science and Game Theory · Computer Science 2016-07-11 Kent E. Morrison

Combinatorial games lead to several interesting, clean problems in algorithms and complexity theory, many of which remain open. The purpose of this paper is to provide an overview of the area to encourage further research. In particular, we…

Computational Complexity · Computer Science 2009-09-25 Erik D. Demaine , Robert A. Hearn

We consider simple stochastic games $\mathcal G$ with energy-parity objectives, a combination of quantitative rewards with a qualitative parity condition. The Maximizer tries to avoid running out of energy while simultaneously satisfying a…

Computer Science and Game Theory · Computer Science 2023-07-13 Mohan Dantam , Richard Mayr