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Economic theory distinguishes between principal-agent settings in which the agent has a private type and settings in which the agent takes a hidden action. Many practical problems, however, involve aspects of both. For example, brand X may…

Computer Science and Game Theory · Computer Science 2021-11-24 Tal Alon , Paul Dütting , Inbal Talgam-Cohen

In this paper, we study multi-agent systems with decentralized resource allocations. Agents have local demand and resource supply, and are interconnected through a network designed to support sharing of the local resource; and the network…

Optimization and Control · Mathematics 2021-03-25 Yijun Chen , Razibul Islam , Elizabeth Ratnam , Ian R. Petersen , Guodong Shi

It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems named social dilemmas. In contrast, humans generally do not have…

Computer Science and Game Theory · Computer Science 2014-01-16 Steven de Jong , Simon Uyttendaele , Karl Tuyls

We consider budget feasible mechanisms for procurement auctions with additive valuation functions. For the divisible case, where agents can be allocated fractionally, there exists an optimal mechanism with approximation guarantee $e/(e-1)$…

Computer Science and Game Theory · Computer Science 2022-09-02 Sophie Klumper , Guido Schäfer

Linear contracts are ubiquitous in practice, yet optimal contract theory often prescribes complex, nonlinear structures. We provide a distributional robustness justification for linear contracts. We study a principal-agent problem where the…

Computer Science and Game Theory · Computer Science 2026-04-28 Shiliang Zuo

In hybrid populations where humans delegate strategic decision-making to autonomous agents, understanding when and how cooperative behaviors can emerge remains a key challenge. We study this problem in the context of energy load management:…

Multiagent Systems · Computer Science 2026-03-13 Isuri Perera , Frits de Nijs , Julian Garcia

The recent framework of performative prediction is aimed at capturing settings where predictions influence the target/outcome they want to predict. In this paper, we introduce a natural multi-agent version of this framework, where multiple…

Machine Learning · Computer Science 2022-01-26 Georgios Piliouras , Fang-Yi Yu

This paper introduces a new negotiating agent model for automated negotiation. We focus on applications without time pressure with multidi-mensional negotiation on both continuous and discrete domains. The agent bidding strategy relies on…

Multiagent Systems · Computer Science 2019-09-23 Cédric Buron , Zahia Guessoum , Sylvain Ductor

The goal of this paper is to provide a survey and application-focused atlas of collective behavior coordination algorithms for multi-agent systems. We survey the general family of collective behavior algorithms for multi-agent systems and…

Multiagent Systems · Computer Science 2021-03-23 Federico Rossi , Saptarshi Bandyopadhyay , Michael T. Wolf , Marco Pavone

Although both data availability and the demand for accurate forecasts are increasing, collaboration between stakeholders is often constrained by data ownership and competitive interests. In contrast to recent proposals within cooperative…

Machine Learning · Computer Science 2026-05-14 Michael Vitali , Pierre Pinson

We review existing approaches to mathematical modeling and analysis of multi-agent systems in which complex collective behavior arises out of local interactions between many simple agents. Though the behavior of an individual agent can be…

Robotics · Computer Science 2007-05-23 Kristina Lerman , Aram Galstyan , Tad Hogg

This paper investigates agreement protocols over cooperative and cooperative--antagonistic multi-agent networks with coupled continuous-time nonlinear dynamics. To guarantee convergence for such systems, it is common in the literature to…

Multiagent Systems · Computer Science 2015-08-06 Ziyang Meng , Guodong Shi , Karl Henrik Johansson

Independent reinforcement learning algorithms have no theoretical guarantees for finding the best policy in multi-agent settings. However, in practice, prior works have reported good performance with independent algorithms in some domains…

Multiagent Systems · Computer Science 2021-11-02 Ken Ming Lee , Sriram Ganapathi Subramanian , Mark Crowley

The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we propose a theoretical framework for aligning economic interests…

Machine Learning · Computer Science 2024-07-03 Jibang Wu , Siyu Chen , Mengdi Wang , Huazheng Wang , Haifeng Xu

Multi-agent approach has become popular in computer science and technology. However, the conventional models of multi-agent and multicomponent systems implicitly or explicitly assume existence of absolute time or even do not include time in…

Multiagent Systems · Computer Science 2017-11-23 Mark Burgin

Stable matching is a fundamental area with many practical applications, such as centralised clearinghouses for school choice or job markets. Recent work has introduced the paradigm of near-feasibility in capacitated matching settings, where…

Computer Science and Game Theory · Computer Science 2026-02-12 Frederik Glitzner

We study the \emph{Submodular Welfare Problem} (SWP), where items are partitioned among agents with monotone submodular utilities to maximize the total welfare under \emph{bandit feedback}. Classical SWP assumes full value-oracle access,…

Computer Science and Game Theory · Computer Science 2026-02-19 Subham Pokhriyal , Shweta Jain , Vaneet Aggarwal

Today's top advertisers typically manage hundreds of campaigns simultaneously and consistently launch new ones throughout the year. A crucial challenge for marketing managers is determining the optimal allocation of limited budgets across…

Machine Learning · Statistics 2024-09-04 Lin Ge , Yang Xu , Jianing Chu , David Cramer , Fuhong Li , Kelly Paulson , Rui Song

The current art in optimal combinatorial auctions is limited to handling the case of single units of multiple items, with each bidder bidding on exactly one bundle (single minded bidders). This paper extends the current art by proposing an…

Computer Science and Game Theory · Computer Science 2010-04-27 Sujit Gujar , Y Narahari

We study a two-period moral hazard problem; there are two agents, with action sets that are unknown to the principal. The principal contracts with each agent sequentially, and seeks to maximize the worst-case discounted sum of payoffs,…

Theoretical Economics · Economics 2024-02-15 Chang Liu