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Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products,…

Computer Science and Game Theory · Computer Science 2019-05-08 Omer Ben-Porat , Moshe Tennenholtz

We propose a simple yet rich model to extend the notions of Nash equilibria and correlated equilibria of strategic games to the quantum setting, in which we then study the relations between classical and quantum equilibria. Unlike the…

Quantum Physics · Physics 2015-03-17 Shengyu Zhang

We propose a deep neural network-based algorithm to identify the Markovian Nash equilibrium of general large $N$-player stochastic differential games. Following the idea of fictitious play, we recast the $N$-player game into $N$ decoupled…

Optimization and Control · Mathematics 2020-06-08 Jiequn Han , Ruimeng Hu

Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

Computer Science and Game Theory · Computer Science 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

We study multi-strategies in multiplayer reachability games played on finite graphs. A multi-strategy prescribes a set of possible actions, instead of a single action as usual strategies: it represents a set of all strategies that are…

Computer Science and Game Theory · Computer Science 2024-11-21 Aline Goeminne , Benjamin Monmege

We consider multi-agent decision making, where each agent optimizes its cost function subject to constraints. Agents' actions belong to a compact convex Euclidean space and the agents' cost functions are coupled. We propose a distributed…

Optimization and Control · Mathematics 2016-12-01 Tatiana Tatarenko , Maryam Kamgarpour

Consider a 2-player normal-form game repeated over time. We introduce an adaptive learning procedure, where the players only observe their own realized payoff at each stage. We assume that agents do not know their own payoff function, and…

Computer Science and Game Theory · Computer Science 2013-06-13 Mario Bravo , Mathieu Faure

It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that players in a game may desire to balance maximization of payoff with…

Computer Science and Game Theory · Computer Science 2015-03-13 Hubie Chen

We study the performance of Fictitious Play, when used as a heuristic for finding an approximate Nash equilibrium of a 2-player game. We exhibit a class of 2-player games having payoffs in the range [0,1] that show that Fictitious Play…

Computer Science and Game Theory · Computer Science 2011-03-22 Paul W. Goldberg , Rahul Savani , Troels Bjerre Sorensen , Carmine Ventre

We consider an extension of strategic normal form games with a phase before the actual play of the game, where players can make binding offers for transfer of utilities to other players after the play of the game, contingent on the…

Computer Science and Game Theory · Computer Science 2013-11-19 Valentin Goranko , Paolo Turrini

Game-theoretic concepts have been extensively studied in economics to provide insight into competitive behaviour and strategic decision making. As computing systems increasingly involve concurrently acting autonomous agents, game-theoretic…

Formal Languages and Automata Theory · Computer Science 2022-07-01 Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos , Rui Yan

In this paper, we study the problem of learning the set of pure strategy Nash equilibria and the exact structure of a continuous-action graphical game with quadratic payoffs by observing a small set of perturbed equilibria. A…

Computer Science and Game Theory · Computer Science 2019-11-12 Adarsh Barik , Jean Honorio

We present a new approach to solving games with a countably or uncountably infinite number of players. Such games are often used to model multiagent systems with a large number of agents. The latter are frequently encountered in economics,…

Computer Science and Game Theory · Computer Science 2025-01-17 Carlos Martin , Tuomas Sandholm

Stochastic differential games have been used extensively to model agents' competitions in Finance, for instance, in P2P lending platforms from the Fintech industry, the banking system for systemic risk, and insurance markets. The recently…

Optimization and Control · Mathematics 2021-03-23 Jiequn Han , Ruimeng Hu , Jihao Long

We consider the problem of computing a mixed-strategy generalized Nash equilibrium (MS-GNE) for a class of games where each agent has both continuous and integer decision variables. Specifically, we propose a novel Bregman…

Optimization and Control · Mathematics 2022-06-14 Wicak Ananduta , Sergio Grammatico

Decision-making for autonomous driving is challenging, considering the complex interactions among multiple traffic agents (e.g., autonomous vehicles (AVs), human drivers, and pedestrians) and the computational load needed to evaluate these…

Systems and Control · Electrical Eng. & Systems 2023-11-13 Mushuang Liu , Ilya Kolmanovsky , H. Eric Tseng , Suzhou Huang , Dimitar Filev , Anouck Girard

We study a game between two firms in which each provide a service based on machine learning. The firms are presented with the opportunity to purchase a new corpus of data, which will allow them to potentially improve the quality of their…

Computer Science and Game Theory · Computer Science 2019-05-24 Jinshuo Dong , Hadi Elzayn , Shahin Jabbari , Michael Kearns , Zachary Schutzman

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 present an algorithm that identifies the reasoning patterns of agents in a game, by iteratively examining the graph structure of its Multi-Agent Influence Diagram (MAID) representation. If the decision of an agent participates in no…

Computer Science and Game Theory · Computer Science 2012-06-18 Dimitrios Antos , Avi Pfeffer

In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment. In multi-player Markov games (MGs), however, the interaction is non-stationary due to the behaviors of other players, so…

Computer Science and Game Theory · Computer Science 2021-10-19 Yuanheng Zhu , Dongbin Zhao , Mengchen Zhao , Dong Li