Content area

Abstract

This paper shows how genetic programming (an area under the umbrella of evolutionary computation) can be applied in two out of the six RL 2009 benchmark problems, such as the Acrobot and the Generalised Helicopter Hovering. The paper is organised as follows: the next section provides a short introduction to the field of genetic programming and how it can be seen as an automatic generator of controllers. Section 3 describes the acrobot problem and the experiments and results obtained by using a genetic programming approach. Section 4 describes the generalised helicopter hovering problem and the simulation results obtained using a controller evolved by genetic programming. The same section compares the genetic programming controller with the winner of the 2008 reinforcement learning competition. Finally, Section 5 summarises this work and outlines future desirable research.

Details

Title
GENETIC PROGRAMMING AS A SOLVER TO CHALLENGING REINFORCEMENT LEARNING PROBLEMS
Publication title
Volume
20
Issue
3
Pages
351-379
Number of pages
29
Publication year
2013
Publication date
2013
Publisher
Nova Science Publishers, Inc.
Place of publication
Huttington
Country of publication
United States
Publication subject
ISSN
15356698
Source type
Scholarly Journal
Language of publication
English
Document type
Feature
Document feature
Diagrams; Tables; Equations; Graphs; References
ProQuest document ID
1625960097
Document URL
https://www.proquest.com/scholarly-journals/genetic-programming-as-solver-challenging/docview/1625960097/se-2?accountid=208611
Copyright
Copyright Nova Science Publishers, Inc. 2013
Last updated
2023-11-25
Database
ProQuest One Academic