Learning and evolution in neural networks
Adaptive Behavior
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Embodied Evolution with a New Genetic Programming Variation Algorithm
ICAS '08 Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Embodied evolution and learning: the neglected timing of maturation
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
The balance between initial training and lifelong adaptation in evolving robot controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Open-ended evolutionary robotics: an information theoretic approach
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Racing to improve on-line, on-board evolutionary robotics
Proceedings of the 13th annual conference on Genetic and evolutionary computation
On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
A comparison between different encoding strategies for snake-like robot controllers
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Evolution of station keeping as a response to flows in an aquatic robot
Proceedings of the 15th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
This paper reports on a feasibility study into the evolution of robot controllers during the actual operation of robots (on-line), using only the computational resources within the robots themselves (on-board). We identify the main challenges that these restrictions imply and propose mechanisms to handle them. The resulting algorithm is evaluated in a hybrid system, using the actual robots' processors interfaced with a simulator that represents the environment. The results show that the proposed algorithm is indeed feasible and the particular problems we encountered during this study give hints for further research.