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Paper Abstract and Keywords
Presentation 2012-03-13 11:45
Efficient Task Allocation by Learning and Reorganization of Hierarchical Agent Network Based on Observed Delay
Kazuki Urakawa, Toshiharu Sugawara (Waseda Univ.) AI2011-45
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a method for efficient task allocation by changing the network structure among agents to adapt to the environmental changes. As services in a distributed environment like the Internet often consist of a number of service elements, the task for the service can be modeled as a set of subtasks and can be achieved by executing all the subtasks. So they are executed in appropriate agents that have required resources and/or functionalities to In order to realize the corresponding services, this type of problem is formulated as a team formation problem in which all (sub)tasks are allocated to a number of agents (team). A number of studies addressed this issue; proposed a method by adding links between agents based on the amount of unused resources in a task-oriented domain. However, this kind of methods have the drawback that the reorganization stops in an earlier stage of learning. It also retains the generated links, but when the types of the requested tasks change, it could not adapt quickly to the new disribution of incoming tasks. The method proposed in this paper generates a new link that can allocate tasks to unbusy agents and eliminates the link that is hardly used based on the numbers of the processed tasks in each agent. We experimentally show that the proposed method can exhibit higher performance and adapt to the changes of requested task patterns.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-agent reinforcement learning / Distributed cooperative system / Reorganization / Team formation / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 474, AI2011-45, pp. 13-18, March 2012.
Paper # AI2011-45 
Date of Issue 2012-03-06 (AI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Conference Date 2012-03-11 - 2012-03-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Jozankei View Hotel 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Social System and Information Technology 
Paper Information
Registration To AI 
Conference Code 2012-03-AI-ICS-KBS-SAI-DOCMAS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Efficient Task Allocation by Learning and Reorganization of Hierarchical Agent Network Based on Observed Delay 
Sub Title (in English)  
Keyword(1) Multi-agent reinforcement learning  
Keyword(2) Distributed cooperative system  
Keyword(3) Reorganization  
Keyword(4) Team formation  
1st Author's Name Kazuki Urakawa  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Toshiharu Sugawara  
2nd Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2012-03-13 11:45:00 
Presentation Time 30 minutes 
Registration for AI 
Paper # AI2011-45 
Volume (vol) vol.111 
Number (no) no.474 
Page pp.13-18 
Date of Issue 2012-03-06 (AI) 

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