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Bargaining networks model the behavior of a set of players that need to reach pairwise agreements for making profits. Nash bargaining solutions are special outcomes of such games that are both stable and balanced. Kleinberg and Tardos…

Computer Science and Game Theory · Computer Science 2010-05-10 Yashodhan Kanoria , Mohsen Bayati , Christian Borgs , Jennifer Chayes , Andrea Montanari

Continual learning is often motivated by the idea, known as the big world hypothesis, that "the world is bigger" than the agent. Recent problem formulations capture this idea by explicitly constraining an agent relative to the environment.…

Artificial Intelligence · Computer Science 2025-12-30 Alex Lewandowski , Adtiya A. Ramesh , Edan Meyer , Dale Schuurmans , Marlos C. Machado

In human-AI interaction, a prominent goal is to attain human`s desirable outcome with the assistance of AI agents, which can be ideally delineated as a problem of seeking the optimal Nash Equilibrium that matches the human`s desirable…

Artificial Intelligence · Computer Science 2024-05-28 Anjie Liu , Jianhong Wang , Haoxuan Li , Xu Chen , Jun Wang , Samuel Kaski , Mengyue Yang

We consider shared workspace scenarios with humans and robots acting to achieve independent goals, termed as parallel play. We model these as general-sum games and construct a framework that utilizes the Nash equilibrium solution concept to…

Artificial Intelligence · Computer Science 2020-06-11 Shray Bansal , Jin Xu , Ayanna Howard , Charles Isbell

Many applications of RCTs involve the presence of multiple treatment administrators -- from field experiments to online advertising -- that compete for the subjects' attention. In the face of competition, estimating a causal effect becomes…

Computer Science and Game Theory · Computer Science 2024-06-06 Ana-Andreea Stoica , Vivian Y. Nastl , Moritz Hardt

In many multi-agent settings, participants can form teams to achieve collective outcomes that may far surpass their individual capabilities. Measuring the relative contributions of agents and allocating them shares of the reward that…

Machine Learning · Computer Science 2022-08-19 Daphne Cornelisse , Thomas Rood , Mateusz Malinowski , Yoram Bachrach , Tal Kachman

The empirical analysis of discrete complete-information games has relied on behavioral restrictions in the form of solution concepts, such as Nash equilibrium. Choosing the right solution concept is crucial not just for identification of…

Econometrics · Economics 2019-09-23 Nail Kashaev , Bruno Salcedo

The fact that humans cooperate with non-kin in large groups, or with people they will never meet again, is a long-standing evolutionary puzzle with profound implications. Cooperation is linked to altruism, the capacity to perform costly…

Populations and Evolution · Quantitative Biology 2007-05-23 Angel Sanchez , Jose A. Cuesta

The growing adoption of large language models (LLMs) presents potential for deeper understanding of human behaviours within game theory frameworks. Addressing research gap on multi-player competitive games, this paper examines the strategic…

General Economics · Economics 2024-10-04 Siting Estee Lu

Cooperative games can be distinguished as non-cooperative games in which players can freely sign binding agreements to form coalitions. These coalitions inherit a joint strategy set and seek to maximize collective payoffs. When the payoffs…

Theoretical Economics · Economics 2024-04-16 Justin Chan

This paper examines public goods and evaluates the mechanism through the game theory. Public goods are characterized by nonexclusivity and nonrivalry and this creates fundamental challenges for allocation. We analyze why competitive markets…

Theoretical Economics · Economics 2025-11-20 Yash Prajapati

We study the problem of allocating indivisible items to budget-constrained agents, aiming to provide fairness and efficiency guarantees. Specifically, our goal is to ensure that the resulting allocation is envy-free up to any item (EFx)…

Computer Science and Game Theory · Computer Science 2023-08-04 Marius Garbea , Vasilis Gkatzelis , Xizhi Tan

Over the years, numerous experiments have been accumulated to show that cooperation is not casual and depends on the payoffs of the game. These findings suggest that humans have attitude to cooperation by nature and the same person may act…

Computer Science and Game Theory · Computer Science 2013-09-11 Valerio Capraro

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

In many two-sided markets, the parties to be matched have incomplete information about their characteristics. We consider the settings where the parties engaged are extremely patient and are interested in long-term partnerships. Hence, once…

Computer Science and Game Theory · Computer Science 2019-08-30 Kartik Ahuja , Mihaela van der Schaar

Multi-agent Reinforcement Learning (MARL) is a powerful tool for training autonomous agents acting independently in a common environment. However, it can lead to sub-optimal behavior when individual incentives and group incentives diverge.…

Artificial Intelligence · Computer Science 2024-01-30 Andreas A. Haupt , Phillip J. K. Christoffersen , Mehul Damani , Dylan Hadfield-Menell

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a…

Computer Science and Game Theory · Computer Science 2014-01-16 Radu Jurca , Boi Faltings

We investigate both stationary and time-varying, nonmonotone generalized Nash equilibrium problems that exhibit symmetric interactions among the agents, which are known to be potential. As may happen in practical cases, however, we envision…

Optimization and Control · Mathematics 2024-07-09 Filippo Fabiani , Andrea Simonetto , Paul J. Goulart

Standard game theory assumes that the structure of the game is common knowledge among players. We relax this assumption by considering extensive games where agents may be unaware of the complete structure of the game. In particular, they…

Computer Science and Game Theory · Computer Science 2007-05-23 Joseph Y. Halpern , Leandro C. Rêgo

Most work in game theory assumes that players are perfect reasoners and have common knowledge of all significant aspects of the game. In earlier work, we proposed a framework for representing and analyzing games with possibly unaware…

Computer Science and Game Theory · Computer Science 2007-07-17 Leandro C. Rego , Joseph Y. Halpern