Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Designing application-specific neural networks using the genetic algorithm
Advances in neural information processing systems 2
A qualitative way of solving the pole balancing problem
Machine intelligence 12
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Designing Neural Networks using Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Genetic Algorithm for Inducing Control Rules for a Dynamic System
Proceedings of the 3rd International Conference on Genetic Algorithms
A Topology Exploiting Genetic Algorithm to Control Dynamic Systems
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Diagnosis Based on Genetic Algorithms and Fuzzy Logic in NPPs
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Structured genetic algorithm representations for neural network evolution
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
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This paper describes the application of the Structured Genetic Algorithm (sGA)to design neuro-controllers for an unstable physical system. In particular, the approach uses a single unified genetic process to automatically evolve completeneural nets (both architectures and their weights) for controlling a simulatedpole-cart system. Experimental results demonstrate theeffectiveness of the sGA-evolved neuro-controllers for the task—to keep thepole upright (within a specified vertical angle) and the cart within thelimits of the given track.