Analysis of Coordination Structures of Partially Observing Cooperative Agents by Multi-agent Deep Q-Learning

Ken Smith, Yuki Miyashita, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We compare the coordination structures of agents using different types of inputs for their deep Q-networks (DQNs) by having agents play a distributed task execution game. The efficiency and performance of many multi-agent systems can be significantly affected by the coordination structures formed by agents. One important factor that may affect these structures is the information provided to an agent’s DQN. In this study, we analyze the differences in coordination structures in an environment involving walls to obstruct visibility and movement. Additionally, we introduce a new DQN input, which performs better than past inputs in a dynamic setting. Experimental results show that agents with their absolute locations in their DQN input indicate a granular level of labor division in some settings, and that the consistency of the starting locations of agents significantly affects the coordination structures and performances of agents.

Original languageEnglish
Title of host publicationPRIMA 2020
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 23rd International Conference, 2020, Proceedings
EditorsTakahiro Uchiya, Quan Bai, Iván Marsá Maestre
PublisherSpringer Science and Business Media Deutschland GmbH
Pages150-164
Number of pages15
ISBN (Print)9783030693213
DOIs
Publication statusPublished - 2021
Event23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 - Virtual, Online
Duration: 2020 Nov 182020 Nov 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12568 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020
CityVirtual, Online
Period20/11/1820/11/20

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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