Investigations into Lamarckism, Baldwinism and Local Search in Grammatical Evolution Guided by Reinforcement

Authors

  • Jack Mario Mingo Computer Science Department, Universidad Carlos III de Madrid, Madrid
  • Ricardo Aler Computer Science Department, Universidad Carlos III de Madrid, Madrid
  • Darío Maravall Artificial Intelligence Department,Universidad Politécnica de Madrid, Madrid
  • Javier de Lope Applied Intelligent Systems Department, Universidad POlitécnica de Madrid, Madrid

Keywords:

Hybrid algorithms, grammatical evolution, Lamarckism, Baldwinism

Abstract

Grammatical Evolution Guided by Reinforcement is an extension of Grammatical Evolution that tries to improve the evolutionary process adding break a learning process for all the individuals in the population. With this aim, each individual is given a chance to learn through a reinforcement learning mechanism during its lifetime. The learning process is completed with a Lamarckian mechanism in which an original genotype is replaced by the best learnt genotype for the individual. In a way, Grammatical Evolution Guided by Reinforcement shares an important feature with other hybrid algorithms, i.e. global search in the evolutionary process combined with local search in the learning process. In this paper the role of the Lamarck Hypothesis is reviewed and a solution inspired only in the Baldwin effect is included as well. Besides, different techniques about the trade-off between exploitation and exploration in the reinforcement learning step followed by Grammatical Evolution Guided by Reinforcement are studied. In order to evaluate the results, the system is applied on two different domains: a simple autonomous navigation problem in a simulated Kephera robot and a typical Boolean function problem.

Downloads

Download data is not yet available.

Downloads

Published

2013-07-10

How to Cite

Mingo, J. M., Aler, R., Maravall, D., & de Lope, J. (2013). Investigations into Lamarckism, Baldwinism and Local Search in Grammatical Evolution Guided by Reinforcement. COMPUTING AND INFORMATICS, 32(3), 595–627. Retrieved from https://www.cai.sk/ojs/index.php/cai/article/view/1735