No Agent Left Behind: Dynamic Fair Division of Multiple Resources

Recently fair division theory has emerged as a promising approach for allocation of multiple computational resources among agents. While in reality agents are not all present in the system simultaneously, previous work has studied static settings where all relevant information is known upfront. Our...

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Bibliographic Details
Published inThe Journal of artificial intelligence research Vol. 51; pp. 579 - 603
Main Authors Kash, I., Procaccia, A. D., Shah, N.
Format Journal Article
LanguageEnglish
Published San Francisco AI Access Foundation 01.01.2014
Subjects
Artificial intelligence
Dynamic models
Multiagent systems
Resource allocation
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Summary:Recently fair division theory has emerged as a promising approach for allocation of multiple computational resources among agents. While in reality agents are not all present in the system simultaneously, previous work has studied static settings where all relevant information is known upfront. Our goal is to better understand the dynamic setting. On the conceptual level, we develop a dynamic model of fair division, and propose desirable axiomatic properties for dynamic resource allocation mechanisms. On the technical level, we construct two novel mechanisms that provably satisfy some of these properties, and analyze their performance using real data. We believe that our work informs the design of superior multiagent systems, and at the same time expands the scope of fair division theory by initiating the study of dynamic and fair resource allocation mechanisms.
ISSN:1076-9757
1076-9757
1943-5037
DOI:10.1613/jair.4405