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|Abstract=Evolutionary Robotics is a collection of heuristics where robotic control systems are developed by following the example of natural evolution. An evolutionary run is performed by mutating the robots’ controllers randomly and selecting for some desired behavioral properties. Overall, these properties should be improved over time leading to a stable increase of fitness. However, random mutations on critical controller parts can lead to a rapid degradation lowering the performance of evolution. This paper presents an approach to reduce the loss of desirable behavior during an evolution process. A notion of age is introduced as a quality criterion to indicate the contribution of parts of a controller to the robot’s overall behavior. To preserve the behavior evolved so far, mutations are channeled to affect controller parts with a lower age more than those with a higher age. As a result, controller parts that contribute to a good behavior are stabilized and the evolved desirable behavior is maintained. Experiments have been performed in a decentralized online evolutionary scenario with controllers based on finite state machines (FSMs). The results show an improvement in the number of successful evolutions and the number of successfully evolved robots compared to previous studies.
 
|Abstract=Evolutionary Robotics is a collection of heuristics where robotic control systems are developed by following the example of natural evolution. An evolutionary run is performed by mutating the robots’ controllers randomly and selecting for some desired behavioral properties. Overall, these properties should be improved over time leading to a stable increase of fitness. However, random mutations on critical controller parts can lead to a rapid degradation lowering the performance of evolution. This paper presents an approach to reduce the loss of desirable behavior during an evolution process. A notion of age is introduced as a quality criterion to indicate the contribution of parts of a controller to the robot’s overall behavior. To preserve the behavior evolved so far, mutations are channeled to affect controller parts with a lower age more than those with a higher age. As a result, controller parts that contribute to a good behavior are stabilized and the evolved desirable behavior is maintained. Experiments have been performed in a decentralized online evolutionary scenario with controllers based on finite state machines (FSMs). The results show an improvement in the number of successful evolutions and the number of successfully evolved robots compared to previous studies.
 
|Download=PID1522079.pdf,
 
|Download=PID1522079.pdf,
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|Link=http://ieeexplore.ieee.org/search/srchabstract.jsp?tp=&arnumber=5716366&queryText%3Dage+based+controller+stabilization+in+evolutionary+robotics%26openedRefinements%3D*%26searchField%3DSearch+All
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|DOI Name=10.1109/NABIC.2010.5716366
 
|Forschungsgruppe=Effiziente Algorithmen
 
|Forschungsgruppe=Effiziente Algorithmen
 
}}
 
}}
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|Forschungsgebiet=Evolutionäre Robotik
 
|Forschungsgebiet=Evolutionäre Robotik
 
}}
 
}}
Keywords: Evolutionary Robotics; Stabilization; Age; Evolutionary
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age based controller stabilization;behavioral properties;critical controller parts;decentralized online evolutionary scenario;desirable behavior;evolution performance;evolution process;evolutionary robotics;evolutionary run;finite state machines;natural evolution;quality criterion;rapid degradation lowering;robotic control systems;evolutionary computation;finite state machines;stability;
Robotics, Finite State Machine, Decentralized, Online,
 
Stabilization, Age
 

Version vom 27. April 2011, 08:29 Uhr


Age Based Controller Stabilization in Evolutionary Robotics




Published: 2010 Dezember

Buchtitel: 2nd World Congress on Nature and Biologically Inspired Computing (NaBIC)
Seiten: 84 -91
Verlag: IEEE Computer Society
Organisation: Machine Intelligence Research Labs

Referierte Veröffentlichung

BibTeX

Kurzfassung
Evolutionary Robotics is a collection of heuristics where robotic control systems are developed by following the example of natural evolution. An evolutionary run is performed by mutating the robots’ controllers randomly and selecting for some desired behavioral properties. Overall, these properties should be improved over time leading to a stable increase of fitness. However, random mutations on critical controller parts can lead to a rapid degradation lowering the performance of evolution. This paper presents an approach to reduce the loss of desirable behavior during an evolution process. A notion of age is introduced as a quality criterion to indicate the contribution of parts of a controller to the robot’s overall behavior. To preserve the behavior evolved so far, mutations are channeled to affect controller parts with a lower age more than those with a higher age. As a result, controller parts that contribute to a good behavior are stabilized and the evolved desirable behavior is maintained. Experiments have been performed in a decentralized online evolutionary scenario with controllers based on finite state machines (FSMs). The results show an improvement in the number of successful evolutions and the number of successfully evolved robots compared to previous studies.

Download: Media:PID1522079.pdf
Weitere Informationen unter: Link
DOI Link: 10.1109/NABIC.2010.5716366

Verknüpfte Tools

Organic Computing Learning Robots Arena


Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet

Evolutionäre Robotik


age based controller stabilization;behavioral properties;critical controller parts;decentralized online evolutionary scenario;desirable behavior;evolution performance;evolution process;evolutionary robotics;evolutionary run;finite state machines;natural evolution;quality criterion;rapid degradation lowering;robotic control systems;evolutionary computation;finite state machines;stability;