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|Abstract=In this paper, a control system representation based on finite state machines is utilized to build an evolutionary robotic framework where evolution is performed in a swarm of simple robots in an online and onboard manner. Experiments in simulation show that the framework is capable of robustly evolving basic benchmark behaviors like collision avoidance. | |Abstract=In this paper, a control system representation based on finite state machines is utilized to build an evolutionary robotic framework where evolution is performed in a swarm of simple robots in an online and onboard manner. Experiments in simulation show that the framework is capable of robustly evolving basic benchmark behaviors like collision avoidance. | ||
+ | |DOI Name=10.1145/1558109.1558275 | ||
|Forschungsgruppe=Effiziente Algorithmen | |Forschungsgruppe=Effiziente Algorithmen | ||
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Version vom 24. September 2009, 15:51 Uhr
Online and Onboard Evolution of Robotic Behavior Using Finite State Machines
Online and Onboard Evolution of Robotic Behavior Using Finite State Machines
Published: 2009
Mai
Buchtitel: Proceedings Of The 8th International Conference On Autonomous Agents And Multiagent Systems (AAMAS 2009)
Seiten: 1325-1326
Referierte Veröffentlichung
BibTeX
Kurzfassung
In this paper, a control system representation based on finite state machines is utilized to build an evolutionary robotic framework where evolution is performed in a swarm of simple robots in an online and onboard manner. Experiments in simulation show that the framework is capable of robustly evolving basic benchmark behaviors like collision avoidance.
DOI Link: 10.1145/1558109.1558275
Verknüpfte Tools
Organic Computing Learning Robots Arena
Forschungsgruppe
Forschungsgebiet
Organic Computing, Agentensysteme, Evolutionäre Robotik