Seeing the light: artificial evolution, real vision
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
An introduction to genetic algorithms
An introduction to genetic algorithms
Incremental evolution of complex general behavior
Adaptive Behavior - Special issue on environment structure and behavior
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Cooperative Coevolutionary Approach to Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
IEEE Transactions on Neural Networks
Evolution of vision capabilities in embodied virtual creatures
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Genetic representation and evolvability of modular neural controllers
IEEE Computational Intelligence Magazine
| Hi-index | 0.00 |
In this paper we apply incremental evolution for automatic synthesis of neural network controllers for a group of physically connected mobile robots called s-bots The robots should be able to safely and cooperatively perform phototaxis in an arena containing holes We experiment with two approaches to incremental evolution, namely behavioral decomposition and environmental complexity increase Our results are compared with results obtained in a previous study where several non-incremental evolutionary algorithms were tested and in which the evolved controllers were shown to transfer successfully to real robots Surprisingly, none of the incremental evolutionary strategies performs any better than the non-incremental approach We discuss the main reasons for this and why it can be difficult to apply incremental evolution successfully in highly integrated tasks.