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We study the problem of scheduling periodic real-time tasks so as to meet their individual minimum reward requirements. A task generates jobs that can be given arbitrary service times before their deadlines. A task then obtains rewards…

Other Computer Science · Computer Science 2010-07-06 I-Hong Hou , P. R. Kumar

This paper investigates a class of games with large strategy spaces, motivated by challenges in AI alignment and language games. We introduce the hidden game problem, where for each player, an unknown subset of strategies consistently…

Artificial Intelligence · Computer Science 2025-10-07 Gon Buzaglo , Noah Golowich , Elad Hazan

We consider turn-based game arenas for which we investigate uniformity properties of strategies. These properties involve bundles of plays, that arise from some semantical motive. Typically, we can represent constraints on allowed…

Computer Science and Game Theory · Computer Science 2012-12-04 Bastien Maubert , Sophie Pinchinat

We study the quality of outcomes in repeated games when the population of players is dynamically changing and participants use learning algorithms to adapt to the changing environment. Game theory classically considers Nash equilibria of…

Computer Science and Game Theory · Computer Science 2020-05-25 Thodoris Lykouris , Vasilis Syrgkanis , Eva Tardos

In a classical optimal stopping problem the aim is to maximize the expected value of a functional of a diffusion evaluated at a stopping time. This note considers optimal stopping problems beyond this paradigm. We study problems in which…

Probability · Mathematics 2017-08-04 Vicky Henderson , David Hobson , Matthew Zeng

We consider concurrent stochastic games played on graphs with reachability and safety objectives. These games can be solved by value iteration as well as strategy iteration, each of them yielding a sequence of under-approximations of the…

Computer Science and Game Theory · Computer Science 2019-09-19 Julia Eisentraut , Jan Křetínský , Alexej Rotar

Multi-round competitions often double or triple the points awarded in the final round, calling it a bonus, to maximize spectators' excitement. In a two-player competition with $n$ rounds, we aim to derive the optimal bonus size to maximize…

Computer Science and Game Theory · Computer Science 2024-06-10 Zhihuan Huang , Yuqing Kong , Tracy Xiao Liu , Grant Schoenebeck , Shengwei Xu

The best-response dynamics is an example of an evolutionary game where players update their strategy in order to maximize their payoff. The main objective of this paper is to study a stochastic spatial version of this game based on the…

Probability · Mathematics 2014-07-28 Stephen Evilsizor , Nicolas Lanchier

We consider an agent who needs to buy (or sell) a relatively small amount of asset over some fixed short time interval. We work at the highest frequency meaning that we wish to find the optimal tactic to execute our quantity using limit…

Trading and Market Microstructure · Quantitative Finance 2018-03-16 Charles-Albert Lehalle , Othmane Mounjid , Mathieu Rosenbaum

Reactive synthesis is a framework for modeling and automatically synthesizing strategies in robotics, typically through computing a \emph{winning} strategy in a 2-player game between the robot and the environment. Winning strategies,…

Robotics · Computer Science 2024-10-14 Karan Muvvala , Morteza Lahijanian

In game theory, mechanism design is concerned with the design of incentives so that a desired outcome of the game can be achieved. In this paper, we study the design of incentives so that a desirable equilibrium is obtained, for instance,…

Computer Science and Game Theory · Computer Science 2021-06-21 Julian Gutierrez , Muhammad Najib , Giuseppe Perelli , Michael Wooldridge

Additively separable hedonic games and fractional hedonic games have received considerable attention. They are coalition forming games of selfish agents based on their mutual preferences. Most of the work in the literature characterizes the…

Artificial Intelligence · Computer Science 2017-06-29 Michele Flammini , Gianpiero Monaco , Qiang Zhang

We study the emergence of locally suboptimal behavior in finitely repeated games. Locally suboptimal behavior refers to players play suboptimally in some rounds of the repeated game (i.e., not maximizing their payoffs in those rounds) while…

Computer Science and Game Theory · Computer Science 2023-03-30 Yichen Yang , Martin Rinard

Network congestion games are a convenient model for reasoning about routing problems in a network: agents have to move from a source to a target vertex while avoiding congestion, measured as a cost depending on the number of players using…

Computer Science and Game Theory · Computer Science 2022-07-05 Aline Goeminne , Nicolas Markey , Ocan Sankur

Imitation is simple behavior which uses successful actions of others in order to deal with one's own problems. Because success of imitation generally depends on whether profit of an imitating agent coincides with those of other agents or…

Physics and Society · Physics 2023-01-23 Masahiko Ueda

Strategy iteration is a technique frequently used for two-player games in order to determine the winner or compute payoffs, but to the best of our knowledge no general framework for strategy iteration has been considered. Inspired by…

Logic in Computer Science · Computer Science 2022-12-14 Paolo Baldan , Richard Eggert , Barbara König , Tommaso Padoan

We study the class of reach-avoid dynamic games in which multiple agents interact noncooperatively, and each wishes to satisfy a distinct target criterion while avoiding a failure criterion. Reach-avoid games are commonly used to express…

Systems and Control · Electrical Eng. & Systems 2022-03-03 Dennis R. Anthony , Duy P. Nguyen , David Fridovich-Keil , Jaime F. Fisac

We consider turn-based stochastic two-player games with a combination of a parity condition that must hold surely, that is in all possible outcomes, and of a parity condition that must hold almost-surely, that is with probability 1. The…

Computer Science and Game Theory · Computer Science 2026-01-08 Laurent Doyen , Shibashis Guha

Soccer is a sparse rewarding game: any smart or careless action in critical situations can change the result of the match. Therefore players, coaches, and scouts are all curious about the best action to be performed in critical situations,…

Machine Learning · Computer Science 2021-09-15 Pegah Rahimian , Afshin Oroojlooy , Laszlo Toka

Consider a two-person zero-sum search game between a hider and a searcher. The hider hides among $n$ discrete locations, and the searcher successively visits individual locations until finding the hider. Known to both players, a search at…

Machine Learning · Statistics 2021-03-18 Jake Clarkson , Kyle Y. Lin , Kevin D. Glazebrook