Name
Title | ||
|---|---|---|
Genetic fuzzy systems to evolve coordination strategies in competitive distributed systems |
Abstract | ||
|---|---|---|
This paper suggests an evolutionary ap- proach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of fuzzy rule-based models. The aim is to evolve data and rule bases to improve agent performance when playing in a com- petitive environment. In this situation, data for learning and tuning are rare and rule base must jointly evolve with the database. We suggest a genetic algorithm whose op- erators use variable length chromosome, a hierarchical relationship among individu- als through fitness, and a scheme that suc- cessively explore and exploits the search space along generations. Evolution of co- ordination strategies uncovers unknown and unexpected agent behaviors and allows a richer analysis of negotiation mechanisms and their role as a coordination protocol. An application concerning an electric power market illustrates the effectiveness of the approach. |
Year | Venue | Keywords |
|---|---|---|
2003 | EUSFLAT Conf. | mul- tiagent systems.,genetic fuzzy systems,coordi- nation strategies,distributed systems,rule based,competitive strategy,electric power,distributed system,search space,genetic algorithm |
Field | DocType | Citations |
Neuro-fuzzy,Intelligent decision support system,Computer science,Exploit,Artificial intelligence,Adaptive neuro fuzzy inference system,Genetic algorithm,Genetic fuzzy systems,Fuzzy rule,Negotiation | Conference | 1 |
PageRank | References | Authors |
0.38 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Walter | 1 | 15 | 2.85 |
| Fernando A. C. Gomide | 2 | 55 | 46.95 |