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Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04)
New York City, New York, USA
July 19-July 23
ISBN: 0-7695-2092-8
Prasanna Lokuge, Monash University
Damminda Alahakoon, Monash University
Faster turnaround time of vessels and high berth productivity are paramount important factors of any container terminals in assuring competitive advantage in the shipping industry. The Paper proposes a hybrid BDI agent model with Neural Networks and Adaptive Neurofuzzy Inference system (ANFIS) in dealing with complex environments such as operations in container terminal in the shipping industry. Hybrid model is emphasized to improve the learning capabilities of the generic BDI agents. A plan Tuple: PLAN ⧼ B, D, I, SF, TY ⧽ is introduced in handling plans in the intention structure where, B- Beliefs, D - Desires I - intentions, ST - success factor and TY for the type of the plan. Learning capabilities and handling partially successful goal states in the BDI agent model have been improved with the introduction of the hybrid architecture suggested.
Citation:
Prasanna Lokuge, Damminda Alahakoon, "Hybrid BDI Agents with ANFIS in Identifying Goal Success Factor in a Container Terminal Application," aamas, vol. 3, pp.1222-1223, Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04), 2004
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