Sciweavers

Share
GECCO
2007
Springer

Evolving controllers for simulated car racing using object oriented genetic programming

9 years 1 months ago
Evolving controllers for simulated car racing using object oriented genetic programming
Several different controller representations are compared on a non-trivial problem in simulated car racing, with respect to learning speed and final fitness. The controller representations are based either on neural networks or genetic programming, and also differ in regards to whether they allow for stateful controllers or just reactive ones. Evolved GP trees are analysed, and attempts are made at explaining the performance differences observed. TRACK: GENETIC PROGRAMMING Categories and Subject Descriptors I.2 [ARTIFICIAL INTELLIGENCE]: Automatic Programming Keywords Evolutionary robotics, neural networks, Object-Oriented genetic programming, Subtree macro-mutation, Homologous uniform crossover
Alexandros Agapitos, Julian Togelius, Simon M. Luc
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Alexandros Agapitos, Julian Togelius, Simon M. Lucas
Comments (0)
books