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It’s fate : A self-organising evolutionary algorithm

Attachments

Author: Bim, J. · Karafotias, G. · Smit, S.K. · Eiben, A.E. · Haasdijk, E.
Type:article
Date:2012
Publisher: Springer
Place: Berlin : [etc]
Source:Coello Coello, C.A.Cutello, V.Deb, K.et al, Parallel Problem Solving from Nature - PPSN XII : 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II, 185-194
series:
Lecture Notes in Computer Science
Identifier: 465785
doi: doi:10.1007/978-3-642-32964-7_19
Keywords: Robotics · Robotics · Robot swarms · Fate agents · On-line evolution · Evoluionary algorithms · Defence Research · Defence, Safety and Security · Organisation · MSG - Modelling Simulation & Gaming · BSS - Behavioural and Societal Sciences

Abstract

We introduce a novel evolutionary algorithm where the centralized oracle –the selection-reproduction loop– is replaced by a distributed system of Fate Agents that autonomously perform the evolutionary operations. This results in a distributed, situated, and self-organizing EA, where candidate solutions and Fate Agents co-exist and co-evolve. Our motivation comes from evolutionary swarm robotics where candidate solutions evolve in real time and space. As a first proofof- concept, however, here we test the algorithm with abstract function optimization problems. The results show that the Fate Agents EA is capable of evolving good solutions and it can cope with noise and changing fitness landscapes. Furthermore, an analysis of algorithm behavior also shows that this EA successfully regulates population sizes and adapts its parameters.