← Back to papers
2020 AAAI AAAI 2020

Fairness Does Not Imply Satisfaction (Student Abstract)

Abstract

Abstract Fair division is a subfield of multiagent systems that is concerned with object distribution. When objects are indivisible, the Maximin Share Guarantee (MMS) is a desirable fairness notion; however, it is not guaranteed to exist. While MMS allocations may not always exist, a relaxation of MMS is guaranteed to exist. We show that there exists a family of instances for which this relaxation fails to guarantee the MMS value for all but a small constant number of agents.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🧭 Keyword Pioneer — fairness notion
🐝 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

Andrew Searns , Hadi Hosseini

Topics

Artificial Intelligence > Core AI > Multi-Agent Systems Machine Learning > Application Areas > Risk Management Artificial Intelligence > Core AI > Game Theory Machine Learning > Learning Types > Fairness

Keywords

fair division maximin share algorithmic game theory multi-agent system fairness notion
Download PDF

Related papers

Enhancing Pointer Network for Sentence Ordering with Pairwise Ordering Predictions 2020
CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning 2020
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention 2020
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy 2020
Multi-Point Semantic Representation for Intent Classification 2020