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Cooperation Between Agents to Evolve Complete Programs
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Author(s): Ricardo Aler (Universidad Carlos III Madrid, Spain), David Camacho (Universidad Carlos III Madrid, Spain)and Alfredo Moscardini (University of Sunderland, UK)
Copyright: 2003
Pages: 16
Source title:
Intelligent Agent Software Engineering
Source Author(s)/Editor(s): Valentina Plekhanova (University of Sunderland, UK)
DOI: 10.4018/978-1-59140-046-2.ch010
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Abstract
In this paper, we present a multiagent system approach with the purpose of building computer programs. Each agent in the multiagent system will be in charge of evolving a part of the program, which in this case, can be the main body of the program or one of its different subroutines. There are two kinds of agents: the manager agent and the genetic programming (GP) agents. The former is in charge of starting the system and returning the results to the user. The GP agents include skills for evolving computer programs, based on the genetic programming paradigm. There are two sorts of GP agents: some can evolve the main body of the program and the others evolve its subroutines. Both kinds of agents cooperate by telling each other their best results found so far, so that the search for a good computer program is made more efficient. In this paper, this multiagent approach is presented and tested empirically.
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