EPMAS: Evolutionary Programming Multi-Agent Systems.
2010
Evolutionary Programming (EP) seems a promising methodology to automatically find programs to solve new computing challenges. The Evolutionary Programming techniques use classical genetic operators (selection, crossover and mutation) to automatically generate programs targeted to solve computing problems or specifications. Among the methodologies related with Evolutionary Programming we can find Genetic Programming, Analytic Programming and Grammatical Evolution. In this paper we present the Evolutionary Programming Multiagent Systems (EPMAS) framework based on Grammatical Evolution (GE) to evolutionary generate Multi-agent systems (MAS) ad-hoc. We also present two case studies in MAS scenarios for applying our EPMAS framework: the predator-prey problem and the Iterative Prisoner’s Dilemma.
Keywords:
- Evolutionary programming
- Machine learning
- Interactive evolutionary computation
- Human-based evolutionary computation
- Functional reactive programming
- Evolutionary acquisition of neural topologies
- Java Evolutionary Computation Toolkit
- Genetic programming
- Genetic representation
- Artificial intelligence
- Computer science
- Theoretical computer science
- Grammatical evolution
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