Object-oriented analysis and design with applications (2nd ed.)
Object-oriented analysis and design with applications (2nd ed.)
Foundations of distributed artificial intelligence
Mechanism design for automated negotiation, and its application to task oriented domains
Artificial Intelligence
KQML as an agent communication language
Software agents
A trade server for electricity e-commerce
Computers in Industry
Determining Successful Negotiation Strategies: An Evolutionary Approach
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
A machine-learning approach to automated negotiation and prospects for electronic commerce
Journal of Management Information Systems - Special issue: Information technology and its organizational impact
Asymmetric negotiation based collaborative product design for component reuse in disparate products
Computers and Industrial Engineering
| Hi-index | 0.00 |
This paper presents an evolutionary negotiation process for power generating and power consuming companies in a distributed electricity market environment. The process is implemented within an electricity agent to best select a negotiation strategy that meets the underlying company objectives and interests. The negotiating agent generates a sequence of improving strategy population as the outcome of a search method 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 and a framework for negotiation is presented with detailed KQML communication primitives that make up the negotiation protocol. Various software technologies have been used for implementation and tested in a C++ environment.