A Coalitional Algorithm for Recursive Delegation

Juan Afanador Leon, Nir Oren

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

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Abstract

Within multi-agent systems, some agents may delegate tasks to other agents for execution. Recursive delegation designates situations where delegated tasks may, in turn, be delegated onwards. In unconstrained environments, recursive delegation policies based on quitting games are known to outperform policies based on multi-armed bandits. In this work, we incorporate allocation rules and rewarding schemes when considering recursive delegation, and reinterpret the quitting-game approach in terms of coalitions, employing the Shapley and Myerson values to guide delegation decisions. We empirically evaluate our extensions and demonstrate that they outperform the traditional multi-armed bandit based approach, while offering a resource efficient alternative to the quitting game heuristic.
Original languageEnglish
Title of host publicationProceedings of PRIMA 2019
Subtitle of host publication Principles and Practice of Multi-Agent Systems
PublisherSpringer
Pages405-422
Volume11873
DOIs
Publication statusE-pub ahead of print - 21 Oct 2019
EventThe 22nd International Conference
on Principles and Practice of Multi-Agent Systems (PRIMA2019)
- Torino, Italy
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
ISSN (Print)0302-9743

Conference

ConferenceThe 22nd International Conference
on Principles and Practice of Multi-Agent Systems (PRIMA2019)
Abbreviated titlePRIMA2019
Country/TerritoryItaly
CityTorino
Period28/10/1931/10/19

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