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In this work, we study the problem of finding Pareto optimal policies in multi-agent reinforcement learning problems with cooperative reward structures. We show that any algorithm where each agent only optimizes their reward is subject to…

Machine Learning · Computer Science 2024-10-28 Bang Giang Le , Viet Cuong Ta

Human preferences are not always represented via complete linear orders: It is natural to employ partially-ordered preferences for expressing incomparable outcomes. In this work, we consider decision-making and probabilistic planning in…

Robotics · Computer Science 2024-10-21 Hazhar Rahmani , Abhishek N. Kulkarni , Jie Fu

Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met. Nevertheless, unexpected or prolonged abnormal events could undermine the grid's…

Systems and Control · Electrical Eng. & Systems 2024-03-29 Guido Cavraro , Joshua Comden , Andrey Bernstein

In social choice theory, anonymity (all agents being treated equally) and neutrality (all alternatives being treated equally) are widely regarded as ``minimal demands'' and ``uncontroversial'' axioms of equity and fairness. However, the ANR…

Computer Science and Game Theory · Computer Science 2023-07-14 Lirong Xia

Direct Preference Optimization (DPO) has emerged as a simple and effective approach for aligning large language models (LLMs) with human preferences, bypassing the need for a learned reward model. Despite its growing adoption, a fundamental…

Machine Learning · Computer Science 2025-11-10 Yu Pan , Zhongze Cai , Guanting Chen , Huaiyang Zhong , Chonghuan Wang

How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of machine learning systems. Stringent parity constraints on…

Artificial Intelligence · Computer Science 2020-12-09 Angie Peng , Jeff Naecker , Ben Hutchinson , Andrew Smart , Nyalleng Moorosi

In rank aggregation, the task is to aggregate multiple weighted input rankings into a single output ranking. While numerous methods, so-called social welfare functions (SWFs), have been suggested for this problem, all of the classical SWFs…

Computer Science and Game Theory · Computer Science 2025-08-25 Patrick Lederer

By relaxing the dominating set in three ways (e.g., from "each member beats every non-member" to "each member beats or ties every non-member, with an additional requirement that at least one member beat every non-member"), we propose a new…

Theoretical Economics · Economics 2024-03-26 Fujun Hou

We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We…

Computer Science and Game Theory · Computer Science 2019-04-19 Oren Dean , Yakov Babichenko , Moshe Tennenholtz

The voter process is a classic stochastic process that models the invasion of a mutant trait $A$ (e.g., a new opinion, belief, legend, genetic mutation, magnetic spin) in a population of agents (e.g., people, genes, particles) who share a…

Populations and Evolution · Quantitative Biology 2022-05-04 Loke Durocher , Panagiotis Karras , Andreas Pavlogiannis , Josef Tkadlec

For effective decision support in scenarios with conflicting objectives, sets of potentially optimal solutions can be presented to the decision maker. We explore both what policies these sets should contain and how such sets can be computed…

Artificial Intelligence · Computer Science 2023-07-19 Willem Röpke , Conor F. Hayes , Patrick Mannion , Enda Howley , Ann Nowé , Diederik M. Roijers

Achieving consensus via nearest neighbor rules is an important prerequisite for multi-agent networks to accomplish collective tasks. A common assumption in consensus setup is that each agent interacts with all its neighbors. This paper…

Systems and Control · Electrical Eng. & Systems 2022-06-23 Haibin Shao , Lulu Pan , Mehran Mesbahi , Yugeng Xi , Dewei Li

Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and provide motivations for those choices, and AI agents…

Artificial Intelligence · Computer Science 2025-02-12 Enrico Liscio , Luciano C. Siebert , Catholijn M. Jonker , Pradeep K. Murukannaiah

We consider a social planner faced with a stream of myopic selfish agents. The goal of the social planner is to maximize the social welfare, however, it is limited to using only information asymmetry (regarding previous outcomes) and cannot…

Computer Science and Game Theory · Computer Science 2019-05-15 Lee Cohen , Yishay Mansour

As AI usage becomes more prevalent in social contexts, understanding agent-user interaction is critical to designing systems that improve both individual and group outcomes. We present an online behavioral experiment (N = 243) in which…

Computer Science and Game Theory · Computer Science 2026-02-16 Kehang Zhu , Nithum Thain , Vivian Tsai , James Wexler , Crystal Qian

We study the problem of a decision maker who must provide the best possible treatment recommendation based on an experiment. The desirability of the outcome distribution resulting from the policy recommendation is measured through a…

Econometrics · Economics 2022-04-06 Anders Bredahl Kock , David Preinerstorfer , Bezirgen Veliyev

Human behavioural patterns exhibit selfish or competitive, as well as selfless or altruistic tendencies, both of which have demonstrable effects on human social and economic activity. In behavioural economics, such effects have…

Multiagent Systems · Computer Science 2021-04-28 Jan E. Snellman , Gerardo Iñiguez , János Kertész , R. A. Barrio , Kimmo K. Kaski

Voting rules allow multiple agents to aggregate their preferences in order to reach joint decisions. Perhaps one of the most important desirable properties in this context is Condorcet-consistency, which requires that a voting rule should…

Computer Science and Game Theory · Computer Science 2016-02-26 Felix Brandt , Christian Geist , Dominik Peters

We present a formal language for specifying qualitative preferences over temporal goals and a preference-based planning method in stochastic systems. Using automata-theoretic modeling, the proposed specification allows us to express…

Artificial Intelligence · Computer Science 2021-03-29 Jie Fu

We introduce a model of graph-constrained dynamic choice with reinforcement modeled by positively $\alpha$-homogeneous rewards. We show that its empirical process, which can be written as a stochastic approximation recursion with Markov…

Optimization and Control · Mathematics 2021-07-27 Konstantin Avrachenkov , Vivek S. Borkar , Sharayu Moharir , Suhail M. Shah