Evolving agents in a market simulation platform - A test for distinct meta-heuristics

• Type: Article in International Conference Proceedings Book
• Date: 2005

Authors

Vladimiro Miranda (Author) FEUP; Naing Win Oo (Author) FEUP

Conference proceedings International

Title: Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05

Pages: 482-487

13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05

Arlington, VA, 6 November 2005 through 10 November 2005

Indexing

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering > Electrical engineering

Other information

Authenticus ID: P-007-H4P

DOI: 10.1109/isap.2005.1599311

Abstract (EN): This paper presents a comparison in performance of 3 variants of Genetic Algorithms (GA) vs. 2 variants of Evolutionary Particle Swarm Optimization (EPSO), made in the extremely complex context of a multi-energy market simulation where the behavior of energy retailers is observed. The simulations are on JADE, a FIPA compliant platform based on intelligent autonomous agents running in a cluster of PCs. Each agent formulates its strategy by an inner complex simulation process using a meta-heuristic that tries to define optimum decisions. The results suggest that an EPSO approach is more efficient than GA. © 2005 ISAP.

Language: English

Type (Professor's evaluation): Scientific