2024
AAAI
AAAI 2024
Mixed Fair Division: A Survey
Abstract
Abstract The fair allocation of resources to agents is a fundamental problem in society and has received significant attention and rapid developments from the game theory and artificial intelligence communities in recent years. The majority of the fair division literature can be divided along at least two orthogonal directions: goods versus chores, and divisible versus indivisible resources. In this survey, besides describing the state of the art, we outline a number of interesting open questions in three mixed fair division settings: (i) indivisible goods and chores, (ii) divisible and indivisible goods (i.e., mixed goods), and (iii) fair division of indivisible goods with subsidy.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Mathematics & Optimization
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Game AI
Artificial Intelligence > Core AI > Multi-Agent Systems
Artificial Intelligence > Core AI > Procedural Generation
Mathematics & Optimization > Optimization > Combinatorial Optimization
Artificial Intelligence > Core AI > Game Theory
Machine Learning > Learning Types > Fairness