- author = "Michael Botros",
- title = "Evolving Complex Robotic Behaviors Using Genetic Programming",
- year = "2006",
- booktitle = "Genetic Systems Programming: Theory and Experiences",
- pages = "175--194",
- volume = "13",
- series = "Studies in Computational Intelligence",
- editor = "Nadia Nedjah and Ajith Abraham and Luiza {de Macedo Mourelle}",
- publisher = "Springer",
- address = "Germany",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-29849-5",
-
DOI = "
doi:10.1007/3-540-32498-4_8",
-
abstract = "In this chapter, two possible approaches for evolving
complex behaviours were discussed. In the first
approach, the GP is used to explore possible hierarchy
in the solution through implementing ADF and
maintaining a subroutine library or using neural
networks as primitive functions.
In the second approach, human programmer set the architecture of the robot controller and then the GP is used to evolve each module of this architecture. Two examples of architectures were discussed, the subsumption architecture and action selection architecture. Two experiments were presented to demonstrate this approach. The first used subsumption architecture to control a team of two robots with different capabilities to implement a cooperative behavior. The second experiment used action selection architecture to allow switching between the simpler behaviours that constitute the main behavior",
- notes = "http://www.springer.com/sgw/cda/frontpage/0,11855,5-146-22-92733168-0,00.html",
