Genetic Reinforcement Learning for Neurocontrol Problems
Machine Learning - Special issue on genetic algorithms
A study on the reference electrode standardization technique for a realistic head model
Computer Methods and Programs in Biomedicine
Using feedback in a regulatory network computational device
Proceedings of the 13th annual conference on Genetic and evolutionary computation
ReNCoDe: a regulatory network computational device
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
The squares problem and a neutrality analysis with ReNCoDe
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
A cell-based developmental model to generate robot morphologies
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Genetic programming needs better benchmarks
Proceedings of the 14th annual conference on Genetic and evolutionary computation
The Regulatory Network Computational Device
Genetic Programming and Evolvable Machines
Applying genetic regulatory networks to index trading
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Differential gene expression with tree-adjunct grammars
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Extracting key gene regulatory dynamics for the direct control of mechanical systems
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Annals of Mathematics and Artificial Intelligence
On learning to generate wind farm layouts
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Genetic programming with genetic regulatory networks: genetic programming
Proceedings of the 15th annual conference on Genetic and evolutionary computation
GEARNet: grammatical evolution with artificial regulatory networks
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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We discuss how to use a Genetic Regulatory Network as an evolutionary representation to solve a typical GP reinforcement problem, the pole balancing. The network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network. We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.