Test-score semantics as a basis for a computational approach to the representation of meaning
Literary & Linguistic Computing
Evolutionary Algorithm Approach to Bilateral Negotiations
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
A Web-Based Negotiation Agent Using CBR
Revised Papers from the PRICAI 2000 Workshop Reader, Four Workshops held at PRICAI 2000 on Advances in Artificial Intelligence
Modeling Dialogues Using Argumentation
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Belief Revision for Adaptive Negotiation Agents
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
The development of a multi-agent system for construction claims negotiation
Advances in Engineering Software - Civil-comp 2001
Argumentation-based negotiation
The Knowledge Engineering Review
Predicting partner's behaviour in agent negotiation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Adaptive agent negotiation via argumentation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
| Hi-index | 0.00 |
This paper examines the Argumentation Negotiation of agent as a mechanism for solving the intersection priority problem. We integrated multi-agent automatic negotiation mechanism and argumentation reasoning to apply in selecting vehicle priority problem. Agent's belief is evolved by argumentation-base negotiation, so that an agent can adopt the environment easily and select even better actions. When agents are initially created, they have little knowledge and experience with relatively low capability. They strive to adapt themselves to the changing environment. It is an advantage for agents have a good way to learn and evolve their knowledge. This paper addresses evolution of intelligent agents in transport information system. Fuzzy theory is proposed as evolution mechanisms, and Fuzzy soft goal is introduced to facilitate the evolution process. We have built an agent system to demonstrate our approach.