This paper presents an evolutionary negotiating agent to conduct negotiation tasks between power generating and consuming companies in electricity markets. The agent select the best negotiation strategy that meets the underlying company objectives and interests. It generates a sequence of improving strategy population as the outcome of a search modeled by the selection, crossover, and mutation genetic operators. Agents use a content specification language based on an extended object model to specify the requirements, constraints, and negotiation strategic rules, which are used by the negotiation server to conduct a negotiation. A design architecture for negotiation is presented with KQML communication primitives. Various software technologies have been used for implementation and tested in a C++ environment.
Article
Evolutionary Negotiation Strategies in Emerging Electricity Markets
Computer Science and Engineering
Document Type
Conference Proceeding
Publication Date
1-1-2004
Publisher
Springer
Disciplines
Abstract
Comments
Proceedings of the 7th International Conference on Artificial Intelligence and Soft Computing, Book series: Lecture Notes in Computer Science, ISBN: 978-3-540-22123-4, pp. 1099 – 1104, Poland.
Citation Information
Al-Agtash, S. (2004). Evolutionary Negotiation Strategies in Emerging Electricity Markets. In L. Rutkowski, J. H. Siekmann, R. Tadeusiewicz, & L. A. Zadeh (Eds.), Artificial Intelligence and Soft Computing—ICAISC 2004 (pp. 1099–1104). Springer. https://doi.org/10.1007/978-3-540-24844-6_172