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Similar to the role of Markov decision processes in reinforcement learning, Stochastic Games (SGs) lay the foundation for the study of multi-agent reinforcement learning (MARL) and sequential agent interactions. In this paper, we derive…

Computer Science and Game Theory · Computer Science 2023-01-12 Xiaotie Deng , Ningyuan Li , David Mguni , Jun Wang , Yaodong Yang

We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies need not exist, and may require infinite memory if they do. We provide a complete picture of the exact strategy complexity of…

Logic in Computer Science · Computer Science 2020-07-13 Stefan Kiefer , Richard Mayr , Mahsa Shirmohammadi , Patrick Totzke

Two standard algorithms for approximately solving two-player zero-sum concurrent reachability games are value iteration and strategy iteration. We prove upper and lower bounds of 2^(m^(Theta(N))) on the worst case number of iterations…

Computer Science and Game Theory · Computer Science 2012-03-02 Kristoffer Arnsfelt Hansen , Rasmus Ibsen-Jensen , Peter Bro Miltersen

We consider multi-player graph games with partial-observation and parity objective. While the decision problem for three-player games with a coalition of the first and second players against the third player is undecidable, we present a…

Logic in Computer Science · Computer Science 2014-04-23 Krishnendu Chatterjee , Laurent Doyen

We suggest a novel stochastic-approximation algorithm to compute a symmetric Nash-equilibrium strategy in a general queueing game with a finite action space. The algorithm involves a single simulation of the queueing process with dynamic…

Probability · Mathematics 2023-08-30 Liron Ravner , Ran I. Snitkovsky

We propose a stochastic first-order algorithm to learn the rationality parameters of simultaneous and non-cooperative potential games, i.e., the parameters of the agents' optimization problems. Our technique combines (i.) an active-set step…

Optimization and Control · Mathematics 2023-07-31 Stefan Clarke , Gabriele Dragotto , Jaime Fernández Fisac , Bartolomeo Stellato

We provide a learning-based technique for guessing a winning strategy in a parity game originating from an LTL synthesis problem. A cheaply obtained guess can be useful in several applications. Not only can the guessed strategy be applied…

Artificial Intelligence · Computer Science 2023-05-25 Jan Kretinsky , Tobias Meggendorfer , Maximilian Prokop , Sabine Rieder

Strategic deception is an act of manipulating the opponent's perception to gain strategic advantages. In this paper, we study synthesis of deceptive winning strategies in two-player turn-based zero-sum reachability games on graphs with…

Computer Science and Game Theory · Computer Science 2021-04-26 Abhishek N. Kulkarni , Jie Fu

We define memory-efficient certificates for $\mu$-calculus model checking problems based on the well-known correspondence of the $\mu$-calculus model checking with winning certain parity games. Winning strategies can independently checked,…

Logic in Computer Science · Computer Science 2014-01-09 Martin Hofmann , Harald Ruess

Reactive synthesis is a class of methods to construct a provably-correct control system, referred to as a robot, with respect to a temporal logic specification in the presence of a dynamic and uncontrollable environment. This is achieved by…

Formal Languages and Automata Theory · Computer Science 2020-04-24 Abhishek N. Kulkarni , Jie Fu

Solving parity games is a major building block for numerous applications in reactive program verification and synthesis. While they can be solved efficiently in practice, no known approach has a polynomial worst-case runtime complexity. We…

Computer Science and Game Theory · Computer Science 2023-07-28 Tobias Hecking , Swathy Muthukrishnan , Alexander Weinert

This work considers two-player zero-sum semi-Markov games with incomplete information on one side and perfect observation. At the beginning, the system selects a game type according to a given probability distribution and informs to Player…

Optimization and Control · Mathematics 2021-07-16 Fang Chen , Xianping Guo , Zhong-Wei Liao

Repeated games are difficult to analyze, especially when agents play mixed strategies. We study one-memory strategies in iterated prisoner's dilemma, then generalize the result to k-memory strategies in repeated games. Our result shows that…

Computer Science and Game Theory · Computer Science 2019-02-26 Shiheng Wang , Fangzhen Lin

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

In this paper, we establish the existence of optimal bounded memory strategy profiles in multi-player discounted sum games. We introduce a non-deterministic approach to compute optimal strategy profiles with bounded memory. Our approach can…

Computer Science and Game Theory · Computer Science 2015-09-25 Anshul Gupta , Sven Schewe , Dominik Wojtczak

We introduce a formal notion of masking fault-tolerance between probabilistic transition systems based on a variant of probabilistic bisimulation (named masking simulation). We also provide the corresponding probabilistic game…

Logic in Computer Science · Computer Science 2022-07-06 Pablo F. Castro , Pedro D'Argenio , Luciano Putruele , Ramiro Demasi

We study a class of two-player competitive concurrent stochastic games on graphs with reachability objectives. Specifically, player 1 aims to reach a subset $F_1$ of game states, and player 2 aims to reach a subset $F_2$ of game states…

Systems and Control · Electrical Eng. & Systems 2023-03-24 Chongyang Shi , Shuo Han , Jie Fu

We revisit the coalition structure generation problem in which the goal is to partition the players into exhaustive and disjoint coalitions so as to maximize the social welfare. One of our key results is a general polynomial-time algorithm…

Computer Science and Game Theory · Computer Science 2011-06-21 Haris Aziz , Bart de Keijzer

Markov decision processes (MDP) are finite-state systems with both strategic and probabilistic choices. After fixing a strategy, an MDP produces a sequence of probability distributions over states. The sequence is eventually synchronizing…

Computer Science and Game Theory · Computer Science 2013-11-01 Laurent Doyen , Thierry Massart , Mahsa Shirmohammadi

Consider a very simple class of (finite) games: after an initial move by nature, each player makes one move. Moreover, the players have common interests: at each node, all the players get the same payoff. We show that the problem of…

Computer Science and Game Theory · Computer Science 2007-05-23 Francis Chu , Joseph Y. Halpern