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Applicability of Emergence Engineering to Distributed Systems Scenarios
Abstract
Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.
Citation
@techreport{urn:nbn:de:hebis:34-2009010925609,
author={Zapf, Michael and Weise, Thomas},
title={Applicability of Emergence Engineering to Distributed Systems Scenarios},
year={2009}
}
0500 Oax 0501 Text $btxt$2rdacontent 0502 Computermedien $bc$2rdacarrier 1100 2009$n2009 1500 1/eng 2050 ##0##urn:nbn:de:hebis:34-2009010925609 3000 Zapf, Michael 3010 Weise, Thomas 4000 Applicability of Emergence Engineering to Distributed Systems Scenarios / Zapf, Michael 4030 4060 Online-Ressource 4085 ##0##=u http://nbn-resolving.de/urn:nbn:de:hebis:34-2009010925609=x R 4204 \$dTechnischer Report 4170 Kasseler Informatikschriften ;; 2008, 5 7136 ##0##urn:nbn:de:hebis:34-2009010925609
2009-01-09T08:35:56Z 2009-01-09T08:35:56Z 2009-01-09T08:35:56Z urn:nbn:de:hebis:34-2009010925609 http://hdl.handle.net/123456789/2009010925609 196620 bytes application/pdf eng Urheberrechtlich geschützt https://rightsstatements.org/page/InC/1.0/ Agents Multi-Agent Systems AMAS Emergence Emergence Engineering OEE Robust Self-Organization Genetic Programming Rule-based Genetic Programming RBGP Election Critical Section 004 Applicability of Emergence Engineering to Distributed Systems Scenarios Technischer Report Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach. open access Zapf, Michael Weise, Thomas Kasseler Informatikschriften ;; 2008, 5 Presented at EUMAS'08, the Sixth European Workshop on Multi-Agent Systems Bath, UK, December 18-29, 2008. I.2.6 I.5.0 C.2.2 C.2.4 I.2.11 I.6 Kasseler Informatikschriften 2008, 5
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Urheberrechtlich geschützt