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We prove that zero-sum Dynkin games in continuous time with partial and asymmetric information admit a value in randomised stopping times when the stopping payoffs of the players are general \cadlag measurable processes. As a by-product of…

Probability · Mathematics 2022-06-08 Tiziano De Angelis , Nikita Merkulov , Jan Palczewski

In this article we consider zero and non-zero sum risk-sensitive average criterion games for semi-Markov processes with a finite state space. For the zero-sum case, under suitable assumptions we show that the game has a value. We also…

Optimization and Control · Mathematics 2021-06-10 Arnab Bhabak , Subhamay Saha

This paper studies the finite-time horizon Markov games where the agents' dynamics are decoupled but the rewards can possibly be coupled across agents. The policy class is restricted to local policies where agents make decisions using their…

Computer Science and Game Theory · Computer Science 2023-04-11 Runyu Zhang , Yuyang Zhang , Rohit Konda , Bryce Ferguson , Jason Marden , Na Li

In the paper we consider the controlled continuous-time Markov chain describing the interacting particles system with the finite number of types. The system is controlled by two players with the opposite purposes. The limiting game as the…

Optimization and Control · Mathematics 2014-12-02 Yurii Averboukh

Many security and other real-world situations are dynamic in nature and can be modelled as strictly competitive (or zero-sum) dynamic games. In these domains, agents perform actions to affect the environment and receive observations --…

Computer Science and Game Theory · Computer Science 2020-10-23 Karel Horák , Branislav Bošanský , Vojtěch Kovařík , Christopher Kiekintveld

Semi-Markov model is one of the most general models for stochastic dynamic systems. This paper deals with a two-person zero-sum game for semi-Markov processes. We focus on the expected discounted payoff criterion with state-action-dependent…

Computer Science and Game Theory · Computer Science 2021-03-09 Zhihui Yu , Xianping Guo , Li Xia

State-of-the-art methods for solving 2-player zero-sum imperfect information games rely on linear programming or regret minimization, though not on dynamic programming (DP) or heuristic search (HS), while the latter are often at the core of…

Artificial Intelligence · Computer Science 2022-10-27 Aurélien Delage , Olivier Buffet , Jilles S. Dibangoye , Abdallah Saffidine

We study a two-player, zero-sum, stochastic game with incomplete information on one side in which the players are allowed to play more and more frequently. The informed player observes the realization of a Markov chain on which the payoffs…

Optimization and Control · Mathematics 2013-07-15 Pierre Cardaliaguet , Catherine Rainer , Dinah Rosenberg , Nicolas Vieille

Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in…

Logic in Computer Science · Computer Science 2015-04-14 Paul Hunter , Guillermo A. Pérez , Jean-François Raskin

We introduce a discrete-time search game, in which two players compete to find an object first. The object moves according to a time-varying Markov chain on finitely many states. The players know the Markov chain and the initial probability…

Computer Science and Game Theory · Computer Science 2020-08-28 Benoit Duvocelle , János Flesch , Mathias Staudigl , Dries Vermeulen

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 considers two-player zero-sum finite-horizon Markov games with simultaneous moves. The study focuses on the challenging settings where the value function or the model is parameterized by general function classes. Provably…

Computer Science and Game Theory · Computer Science 2021-11-02 Baihe Huang , Jason D. Lee , Zhaoran Wang , Zhuoran Yang

Partially Observable Markov Games (POMGs) provide a general framework for modeling multi-agent sequential decision-making under asymmetric information. A common approach is to reformulate a POMG as a fully observable Markov game over belief…

Multiagent Systems · Computer Science 2026-04-08 Lan Sang , Chinmay Maheshwari

This paper considers the discounted criterion of nonzero-sum decentralized stochastic games with prospect players. The state and action spaces are finite. The state transition probability is nonstationary. Each player independently controls…

Optimization and Control · Mathematics 2024-05-16 Yiting Wu , Junyu Zhang

In this article we consider risk-sensitive control of semi-Markov processes with a discrete state space. We consider general utility functions and discounted cost in the optimization criteria. We consider random finite horizon and infinite…

Optimization and Control · Mathematics 2021-01-13 Arnab Bhabak , Subhamay Saha

Quantitative games are two-player zero-sum games played on directed weighted graphs. Total-payoff games (that can be seen as a refinement of the well-studied mean-payoff games) are the variant where the payoff of a play is computed as the…

Computer Science and Game Theory · Computer Science 2015-07-15 Thomas Brihaye , Gilles Geeraerts , Axel Haddad , Benjamin Monmege

In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Dirk Lange

We consider two person zero-sum games where the players control, at discrete times {tn} induced by a partition $\Pi$ of R + , a continuous time Markov state process. We prove that the limit of the values v$\Pi$ exist as the mesh of $\Pi$…

Optimization and Control · Mathematics 2016-03-31 Sylvain Sorin

In this paper, we consider the social optimal problem of discrete time finite state space mean field games (referred to as finite mean field games [1]). Unlike the individual optimization of their own cost function in competitive models, in…

Optimization and Control · Mathematics 2024-08-09 Zijia Niu , Sanjin Huang , Lu Ren , Wang Yao , Xiao Zhang

A general model for zero-sum stochastic games with asymmetric information is considered. In this model, each player's information at each time can be divided into a common information part and a private information part. Under certain…

Systems and Control · Electrical Eng. & Systems 2019-12-25 Dhruva Kartik , Ashutosh Nayyar