A general framework for parallel BDI agents in dynamic environments
Web Intelligence and Agent Systems
Shared learning vector quantization in a new agent architecture for intelligent deliberation
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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Strategic planning and dynamism in decision making are essential factors in a vessel berthing application in any container port to assure faster turnaround time and high productivity. BDI agents have been used in many applications with limited capabilities. In this paper, wepropose a new hybrid BDI architecture with learning capacities overcoming some limitations exists in the generic BDI agent model. A new "knowledge Acquisition Model" (KAM) module is proposed with a supervised neural network and Adaptive neuro fuzzy inference system (ANFIS) in the intention reconsideration process of the agent model. Commitment strategy of the new intention reconsideration process is based on the motivation of the state transitions and the effect of belief changes in the environment