Abstract
Vessel berthing operations in a container terminal is a very complex application since environmental changes should be considered in assigning a right berth for a vessel. Dynamic planning capabilities would essentially enhance the quality of the decision making process in the terminals. Limitations in the social ability and learning capabilities of the generic BDI execution cycle have been minimized in the proposed architecture. Paper describes the use of Belief-desires-intention (BDI) agents with neural network and adaptive neuro fuzzy inference system in building the intelligence especially in planning process of the agent. Previous knowledge and the uncertainty issues in the environment are modeled with the use of intelligent tools in the hybrid BDI agent model proposed in the paper. This would essentially improve the adaptability and autonomy features of the BDI agents, which assures better planning, scheduling and improved productivity of the terminal.
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Lokuge, P., Alahakoon, D. (2004). BDI Agents Using Neural Network and Adaptive Neuro Fuzzy Inference for Intelligent Planning in Container Terminals. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_145
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DOI: https://doi.org/10.1007/978-3-540-30499-9_145
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