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AI agents increasingly operate in multi-agent environments where outcomes depend on coordination. We distinguish primary algorithmic monoculture -- baseline action similarity -- from strategic algorithmic monoculture, whereby agents adjust…

Artificial Intelligence · Computer Science 2026-04-14 Gonzalo Ballestero , Hadi Hosseini , Samarth Khanna , Ran I. Shorrer

To achieve an optimal outcome in many situations, agents need to choose distinct actions from one another. This is the case notably in many resource allocation problems, where a single resource can only be used by one agent at a time. How…

Computer Science and Game Theory · Computer Science 2014-02-05 Ludek Cigler , Boi Faltings

Coordination failure reduces match quality among employers and candidates in the job market, resulting in a large number of unfilled positions and/or unstable, short-term employment. Centralized job search engines provide a platform that…

Data Structures and Algorithms · Computer Science 2019-05-14 Amar Saini

Although it has been known since the 1970s that a globally optimal strategy profile in a common-payoff game is a Nash equilibrium, global optimality is a strict requirement that limits the result's applicability. In this work, we show that…

Computer Science and Game Theory · Computer Science 2022-07-08 Scott Emmons , Caspar Oesterheld , Andrew Critch , Vincent Conitzer , Stuart Russell

We study the efficiency of allocations in large markets with a network structure where every seller owns an edge in a graph and every buyer desires a path connecting some nodes. While it is known that stable allocations in such settings can…

Computer Science and Game Theory · Computer Science 2015-10-06 Elliot Anshelevich , Shreyas Sekar

While multi-agent reinforcement learning (MARL) has produced numerous algorithms that converge to Nash or related equilibria, such equilibria are often non-unique and can exhibit widely varying efficiency. This raises a fundamental…

Computer Science and Game Theory · Computer Science 2026-01-29 Runyu Zhang , Gioele Zardini , Asuman Ozdaglar , Jeff Shamma , Na Li

Aligning AI systems with human values remains a fundamental challenge, but does our inability to create perfectly aligned models preclude obtaining the benefits of alignment? We study a strategic setting where a human user interacts with…

Machine Learning · Computer Science 2026-02-04 Natalie Collina , Surbhi Goel , Aaron Roth , Emily Ryu , Mirah Shi

In recent years, data has played an increasingly important role in the economy as a good in its own right. In many settings, data aggregators cannot directly verify the quality of the data they purchase, nor the effort exerted by data…

Computer Science and Game Theory · Computer Science 2019-04-30 Tyler Westenbroek , Roy Dong , Lillian J. Ratliff , S. Shankar Sastry

Entities in multi-agent systems may seek conflicting subobjectives, and this leads to competition between them. To address performance degradation due to competition, we consider a bi-level lottery where a social planner at the high level…

Computer Science and Game Theory · Computer Science 2020-12-04 Hunmin Kim , Minghui Zhu

We study competitive resource allocation problems in which players distribute their demands integrally on a set of resources subject to player-specific submodular capacity constraints. Each player has to pay for each unit of demand a cost…

Computer Science and Game Theory · Computer Science 2014-07-30 Tobias Harks , Max Klimm , Britta Peis

The Hotelling-Downs model is a natural and appealing model for understanding strategic positioning by candidates in elections. In this model, voters are distributed on a line, representing their ideological position on an issue. Each…

Computer Science and Game Theory · Computer Science 2024-12-18 Umang Bhaskar , Soumyajit Pyne

Self-optimizing behaviors can lead to outcomes where collective benefits are ultimately destroyed, a well-known phenomenon known as the ``tragedy of the commons". These scenarios are widely studied using game-theoretic approaches to analyze…

Computer Science and Game Theory · Computer Science 2026-02-25 Yamin Vahmian , Keith Paarporn

With a novel search algorithm or assortment planning or assortment optimization algorithm that takes into account a Bayesian approach to information updating and two-stage assortment optimization techniques, the current research provides a…

Theoretical Economics · Economics 2023-07-19 Dipankar Das

Much work in AI deals with the selection of proper actions in a given (known or unknown) environment. However, the way to select a proper action when facing other agents is quite unclear. Most work in AI adopts classical game-theoretic…

Computer Science and Game Theory · Computer Science 2011-06-24 M. Tennenholtz

We introduce a strategic behavior in reinsurance bilateral transactions, where agents choose the risk preferences they will appear to have in the transaction. Within a wide class of risk measures, we identify agents' strategic choices to a…

Risk Management · Quantitative Finance 2020-03-19 Michail Anthropelos , Tim J. Boonen

We suggest a novel stochastic-approximation algorithm to compute a symmetric Nash-equilibrium strategy in a general queueing game with a finite action space. The algorithm involves a single simulation of the queueing process with dynamic…

Probability · Mathematics 2023-08-30 Liron Ravner , Ran I. Snitkovsky

Multi-agent policy-gradient methods have been shown to converge locally near stable Nash equilibria. Local convergence, however, does not determine which equilibrium is reached. We study this question through basin-entry probability with…

Machine Learning · Computer Science 2026-05-19 Yevhen Shcherbinin , Arina Redina , Maxim Kalpin , Vlad Kochetov

Having fixed capacities, homogeneous products and price sensitive customer purchase decision are primary distinguishing characteristics of numerous revenue management systems. Even with two or three rivals, competition is still highly…

Theoretical Economics · Economics 2022-08-08 Niloofar Fadavi

This paper focuses on the coordination of a large population of dynamic agents with private information over multiple periods. Each agent maximizes the individual utility, while the coordinator determines the market rule to achieve group…

Systems and Control · Computer Science 2015-10-05 Sen Li , Wei Zhang

We study {\em bottleneck congestion games} where the social cost is determined by the worst congestion of any resource. These games directly relate to network routing problems and also job-shop scheduling problems. In typical bottleneck…

Computer Science and Game Theory · Computer Science 2010-10-26 Rajgopal Kannan , Costas Busch , Athanasios Vasilakos