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Large-scale, two-sided matching platforms must find market outcomes that align with user preferences while simultaneously learning these preferences from data. Classical notions of stability (Gale and Shapley, 1962; Shapley and Shubik,…

Machine Learning · Computer Science 2023-02-02 Meena Jagadeesan , Alexander Wei , Yixin Wang , Michael I. Jordan , Jacob Steinhardt

Norms with sanctions have been widely employed as a mechanism for controlling and coordinating the behavior of agents without limiting their autonomy. The norms enforced in a multi-agent system can be revised in order to increase the…

Multiagent Systems · Computer Science 2018-10-26 Davide Dell'Anna , Mehdi Dastani , Fabiano Dalpiaz

Agents rarely act in isolation -- their behavioral history, in particular, is public to others. We seek a non-asymptotic understanding of how a leader agent should shape this history to its maximal advantage, knowing that follower agent(s)…

Computer Science and Game Theory · Computer Science 2019-05-29 Vidya Muthukumar , Anant Sahai

Traditionally, when recommender systems are formalized as multi-armed bandits, the policy of the recommender system influences the rewards accrued, but not the length of interaction. However, in real-world systems, dissatisfied users may…

Machine Learning · Computer Science 2024-02-19 Omer Ben-Porat , Lee Cohen , Liu Leqi , Zachary C. Lipton , Yishay Mansour

Punishment is a common tactic to sustain cooperation and has been extensively studied for a long time. While most of previous game-theoretic work adopt the imitation learning where players imitate the strategies who are better off, the…

Populations and Evolution · Quantitative Biology 2024-12-20 Chenyang Zhao , Guozhong Zheng , Chun Zhang , Jiqiang Zhang , Li Chen

We consider an adversarial online learning setting where a decision maker can choose an action in every stage of the game. In addition to observing the reward of the chosen action, the decision maker gets side observations on the reward he…

Machine Learning · Computer Science 2011-10-26 Shie Mannor , Ohad Shamir

Individuals interact with conspecifics in a number of behavioural contexts or dimensions. Here, we formalise this by considering a social network between n individuals interacting in b behavioural dimensions as a nxnxb multidimensional…

Physics and Society · Physics 2013-05-01 David Lusseau , Louise Barrett , S. Peter Henzi

We study a random game in which two players in turn play a fixed number of moves. For each move, there are two possible choices. To each possible outcome of the game we assign a winner in an i.i.d. fashion with a fixed parameter p. In the…

Probability · Mathematics 2024-09-05 Natalia Cardona-Tobón , Anja Sturm , Jan M. Swart

We consider the classical multi-armed bandit problem, but with strategic arms. In this context, each arm is characterized by a bounded support reward distribution and strategically aims to maximize its own utility by potentially retaining a…

Machine Learning · Computer Science 2025-01-28 Ahmed Ben Yahmed , Clément Calauzènes , Vianney Perchet

Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achieve full control, predict the existence of multiple control…

In the context of using norms for controlling multi-agent systems, a vitally important question that has not yet been addressed in the literature is the development of mechanisms for monitoring norm compliance under partial action…

Multiagent Systems · Computer Science 2016-04-22 Natalia Criado , Jose M. Such

We define new graph parameters, called flip-width, that generalize treewidth, degeneracy, and generalized coloring numbers for sparse graphs, and clique-width and twin-width for dense graphs. The flip-width parameters are defined using…

Combinatorics · Mathematics 2024-03-26 Szymon Toruńczyk

A policy is said to be robust if it maximizes the reward while considering a bad, or even adversarial, model. In this work we formalize two new criteria of robustness to action uncertainty. Specifically, we consider two scenarios in which…

Machine Learning · Computer Science 2019-05-08 Chen Tessler , Yonathan Efroni , Shie Mannor

Coordination games describe social or economic interactions in which the adoption of a common strategy has a higher payoff. They are classically used to model the spread of conventions, behaviors, and technologies in societies. Here we…

Computer Science and Game Theory · Computer Science 2008-12-02 Andrea Montanari , Amin Saberi

We consider a setting where multiple players sequentially choose among a common set of actions (arms). Motivated by a cognitive radio networks application, we assume that players incur a loss upon colliding, and that communication between…

Machine Learning · Computer Science 2019-02-22 Pragnya Alatur , Kfir Y. Levy , Andreas Krause

An elegant characterization of the complexity of constraint satisfaction problems has emerged in the form of the the algebraic dichotomy conjecture of [BKJ00]. Roughly speaking, the characterization asserts that a CSP {\Lambda} is tractable…

Computational Complexity · Computer Science 2015-01-08 Jonah Brown-Cohen , Prasad Raghavendra

A universal feature of human societies is the adoption of systems of rules and norms in the service of cooperative ends. How can we build learning agents that do the same, so that they may flexibly cooperate with the human institutions they…

Artificial Intelligence · Computer Science 2024-02-23 Ninell Oldenburg , Tan Zhi-Xuan

This work lies in the fusion of experimental economics and data mining. It continues author's previous work on mining behaviour rules of human subjects from experimental data, where game-theoretic predictions partially fail to work.…

Computer Science and Game Theory · Computer Science 2012-11-13 Rustam Tagiew

We investigate two paradigms for studying the evolution of cooperation--Prisoner's Dilemma and Snowdrift game in an online friendship network obtained from a social networking site. We demonstrate that such social network has small-world…

Physics and Society · Physics 2009-11-13 Feng Fu , Xiaojie Chen , Lianghuan Liu , Long Wang

We introduce a coevolutionary framework in which punishment intensity dynamically adapts to the fraction of cooperators in the population. Unlike static models, adaptive punishment reshapes the effective payoff landscape, driving…

Physics and Society · Physics 2025-12-11 Xingfu Ke , Hao Yu , Xiao-Pu Han , Yi-Cheng Zhang , Fanyuan Meng