Title of article :
Strengths and synergies of evolved and designed controllers: A study within collective robotics Original Research Article
Author/Authors :
Gianluca Baldassarre، نويسنده , , Stefano Nolfi، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
19
From page :
857
To page :
875
Abstract :
This paper analyses the strengths and weaknesses of self-organising approaches, such as evolutionary robotics, and direct design approaches, such as behaviour-based controllers, for the production of autonomous robotsʹ controllers, and shows how the two approaches can be usefully combined. In particular, the paper proposes a method for encoding evolved neural-network based behaviours into motor schema-based controllers and then shows how these controllers can be modified and combined to produce robots capable of solving new tasks. The method has been validated in the context of a collective robotics scenario in which a group of physically assembled simulated autonomous robots are requested to produce different forms of coordinated behaviours (e.g., coordinated motion, walled-arena exiting, and light pursuing).
Keywords :
self-organisation , Modularity , Genetic algorithms , Neural networks , Potential fields , Multi-variable statistical regression , Motor schema-based controllers
Journal title :
Artificial Intelligence
Serial Year :
2009
Journal title :
Artificial Intelligence
Record number :
1207689
Link To Document :
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