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Related papers: Strategy Improvement for Concurrent Safety Games

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This paper examines multiplayer symmetric constant-sum games with more than two players in a competitive setting, including examples like Mahjong, Poker, and various board and video games. In contrast to two-player zero-sum games,…

Machine Learning · Computer Science 2024-10-04 Jiawei Ge , Yuanhao Wang , Wenzhe Li , Chi Jin

We study Stackelberg equilibria in finitely repeated games, where the leader commits to a strategy that picks actions in each round and can be adaptive to the history of play (i.e. they commit to an algorithm). In particular, we study…

Computer Science and Game Theory · Computer Science 2024-03-08 Natalie Collina , Eshwar Ram Arunachaleswaran , Michael Kearns

The problem of solving a parity game is at the core of many problems in model checking, satisfiability checking and program synthesis. Some of the best algorithms for solving parity game are strategy improvement algorithms. These are global…

Computer Science and Game Theory · Computer Science 2010-06-09 Oliver Friedmann , Martin Lange

Games on graphs provide a natural and powerful model for reactive systems. In this paper, we consider generalized reachability objectives, defined as conjunctions of reachability objectives. We first prove that deciding the winner in such…

Computational Complexity · Computer Science 2012-02-06 Nathanaël Fijalkow , Florian Horn

We study turn-based stochastic zero-sum games with lexicographic preferences over reachability and safety objectives. Stochastic games are standard models in control, verification, and synthesis of stochastic reactive systems that exhibit…

Computer Science and Game Theory · Computer Science 2022-07-21 Krishnendu Chatterjee , Joost-Pieter Katoen , Maximilian Weininger , Tobias Winkler

We study countably infinite stochastic 2-player games with reachability objectives. Our results provide a complete picture of the memory requirements of $\varepsilon$-optimal (resp. optimal) strategies. These results depend on the size of…

Computer Science and Game Theory · Computer Science 2024-07-03 Stefan Kiefer , Richard Mayr , Mahsa Shirmohammadi , Patrick Totzke

Pursuit-evasion scenarios appear widely in robotics, security domains, and many other real-world situations. We focus on two-player pursuit-evasion games with concurrent moves, infinite horizon, and discounted rewards. We assume that the…

Computer Science and Game Theory · Computer Science 2016-08-05 Karel Horák , Branislav Bošanský

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

Two-player graph games have found numerous applications, most notably in the synthesis of reactive systems from temporal specifications, but also in verification. The relevance of infinite-state systems in these areas has lead to…

Logic in Computer Science · Computer Science 2023-11-08 Philippe Heim , Rayna Dimitrova

We study two-player games on finite graphs. Turn-based games have many nice properties, but concurrent games are harder to tame: e.g. turn-based stochastic parity games have positional optimal strategies, whereas even basic concurrent…

Computer Science and Game Theory · Computer Science 2023-11-27 Benjamin Bordais , Patricia Bouyer , Stéphane Le Roux

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

We study two-player multi-weighted reachability games played on a finite directed graph, where an agent, called P1, has several quantitative reachability objectives that he wants to optimize against an antagonistic environment, called P2.…

Computer Science and Game Theory · Computer Science 2025-09-08 Thomas Brihaye , Aline Goeminne

We consider perfect-information reachability stochastic games for 2 players on infinite graphs. We identify a subclass of such games, and prove two interesting properties of it: first, Player Max always has optimal strategies in games from…

Computer Science and Game Theory · Computer Science 2011-06-10 Václav Brožek

In the paper it is proven that the two-players turn-based stochastic game "Risk or Safety" has a unique solution. Both players need to play the same strategy if they want to maximize their winning chances. An analytical method based on the…

Combinatorics · Mathematics 2026-03-03 Rüdiger Jehn

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

Safety is a primary concern when applying reinforcement learning to real-world control tasks, especially in the presence of external disturbances. However, existing safe reinforcement learning algorithms rarely account for external…

Machine Learning · Computer Science 2023-10-12 Zeyang Li , Chuxiong Hu , Shengbo Eben Li , Jia Cheng , Yunan Wang

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

The strategy improvement algorithm for mean payoff games and parity games is a local improvement algorithm, just like the simplex algorithm for linear programs. Their similarity has turned out very useful: many lower bounds on running time…

Computer Science and Game Theory · Computer Science 2025-09-22 Matthew Maat

Sequential decision making using Markov Decision Process underpins many realworld applications. Both model-based and model free methods have achieved strong results in these settings. However, real-world tasks must balance reward…

Machine Learning · Computer Science 2026-04-01 Janaka Chathuranga Brahmanage , Akshat Kumar

Simulation and bisimulation metrics for stochastic systems provide a quantitative generalization of the classical simulation and bisimulation relations. These metrics capture the similarity of states with respect to quantitative…

Computer Science and Game Theory · Computer Science 2015-07-01 Krishnendu Chatterjee , Luca de Alfaro , Rupak Majumdar , Vishwanath Raman