Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

Hybrid BDI Agents with ANFIS in identifying Goal Success Factor in a Container Terminal Application

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.