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This paper investigates value function approximation in the context of zero-sum Markov games, which can be viewed as a generalization of the Markov decision process (MDP) framework to the two-agent case. We generalize error bounds from MDPs…

Artificial Intelligence · Computer Science 2013-01-07 Michail Lagoudakis , Ron Parr

This paper addresses a continuous-time risk-minimizing two-player zero-sum stochastic differential game (SDG), in which each player aims to minimize its probability of failure. Failure occurs in the event when the state of the game enters…

Optimization and Control · Mathematics 2023-08-23 Apurva Patil , Yujing Zhou , David Fridovich-Keil , Takashi Tanaka

Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. The synthesized strategies rely on a perfect measure of time elapse, which is not realistic in…

Computer Science and Game Theory · Computer Science 2024-07-02 Benjamin Monmege , Julie Parreaux , Pierre-Alain Reynier

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

An algorithm is proposed to verify whether a finite game is a weighted potential game (WPG) without pre-knowledge on its weights. Then the algorithm is also applied to find the closest WPG for a given finite game. The concept and criterion…

Computer Science and Game Theory · Computer Science 2021-06-24 Daizhan Cheng , Zhengping Ji

Dynamic games arise when multiple agents with differing objectives choose control inputs to a dynamic system. Dynamic games model a wide variety of applications in economics, defense, and energy systems. However, compared to single-agent…

Optimization and Control · Mathematics 2018-09-25 Bolei Di , Andrew Lamperski

This paper develops a unified framework for zero-sum games in which both the pure strategies and the payoff matrices contain complex-valued entries. By leveraging a linear isomorphism between complex and real vector spaces, we extend key…

General Mathematics · Mathematics 2026-05-21 Raneem Madani , Abdel Lisser , Zeno Toffano

Significant progress has been recently achieved in developing efficient solutions for simple stochastic games (SSGs), focusing on reachability objectives. While reductions from stochastic parity games (SPGs) to SSGs have been presented in…

Computer Science and Game Theory · Computer Science 2025-06-09 Raphaël Berthon , Joost-Pieter Katoen , Zihan Zhou

We study policy optimization algorithms for computing correlated equilibria in multi-player general-sum Markov Games. Previous results achieve $O(T^{-1/2})$ convergence rate to a correlated equilibrium and an accelerated $O(T^{-3/4})$…

Machine Learning · Computer Science 2024-05-03 Yang Cai , Haipeng Luo , Chen-Yu Wei , Weiqiang Zheng

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

We study synthesis problems with constraints in partially observable Markov decision processes (POMDPs), where the objective is to compute a strategy for an agent that is guaranteed to satisfy certain safety and performance specifications.…

Mean Field Games (MFGs) have been introduced to efficiently approximate games with very large populations of strategic agents. Recently, the question of learning equilibria in MFGs has gained momentum, particularly using model-free…

Zero-sum and non-zero-sum (aka general-sum) games are relevant in a wide range of applications. While general non-zero-sum games are computationally hard, researchers focus on the special class of monotone games for gradient-based…

Computer Science and Game Theory · Computer Science 2025-12-03 Ruichen Luo , Sebastian U. Stich , Krishnendu Chatterjee

Decoding strategies play a pivotal role in text generation for modern language models, yet a puzzling gap divides theory and practice. Surprisingly, strategies that should intuitively be optimal, such as Maximum a Posteriori (MAP), often…

Machine Learning · Computer Science 2025-05-20 Sijin Chen , Omar Hagrass , Jason M. Klusowski

Extensive-form games with imperfect recall are an important game-theoretic model that allows a compact representation of strategies in dynamic strategic interactions. Practical use of imperfect recall games is limited due to negative…

Computer Science and Game Theory · Computer Science 2017-05-25 Branislav Bosansky , Jiri Cermak , Karel Horak , Michal Pechoucek

This work considers a stochastic Nash game in which each player solves a parameterized stochastic optimization problem. In deterministic regimes, best-response schemes have been shown to be convergent under a suitable spectral property…

Optimization and Control · Mathematics 2018-02-08 Jinlong Lei , Uday V. Shanbhag , Jong-Shi Pang , Suvrajeet Sen

We consider a zero-sum inspection game, in which a defender positions detectors across a critical system to detect multiple attacks caused by an attacker. We assume that detection is imperfect, and each detector location is associated with…

Computer Science and Game Theory · Computer Science 2025-10-14 Bastián Bahamondes , Mathieu Dahan

In this paper, zero-sum mean-field type games (ZSMFTG) with linear dynamics and quadratic utility are studied under infinite-horizon discounted utility function. ZSMFTG are a class of games in which two decision makers whose utilities sum…

Optimization and Control · Mathematics 2020-09-07 René Carmona , Kenza Hamidouche , Mathieu Laurière , Zongjun Tan

The Stackelberg security game is played between a defender and an attacker, where the defender needs to allocate a limited amount of resources to multiple targets in order to minimize the loss due to adversarial attack by the attacker.…

Computer Science and Game Theory · Computer Science 2022-04-27 Rufan Bai , Haoxing Lin , Xinyu Yang , Xiaowei Wu , Minming Li , Weijia Jia

In this paper, we consider stochastic monotone Nash games where each player's strategy set is characterized by possibly a large number of explicit convex constraint inequalities. Notably, the functional constraints of each player may depend…

Optimization and Control · Mathematics 2023-08-25 Zeinab Alizadeh , Afrooz Jalilzadeh , Farzad Yousefian
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