KES2015 : Keynote Speaker

Prof Ah-Hwee Tan

Nanyang Technological University, Singapore

Knowledge Integration and Reinforcement Learning in Self-Organizing Neural Networks

Abstract:

Knowledge integration and learning are two key issues in designing knowledge-based intelligent systems. This talk will present a family of self-organizing neural networks, collectively known as fusion Adaptive Resonance Theory (fusion ART), for building knowledge-based intelligent systems with real-time learning capabilities. By extending the original Adaptive Resonance Theory (ART) models consisting of a single pattern field into a multi-channel architecture, fusion ART unifies a number of important neural network designs developed over the past decades. Based on a universal set of neural encoding and adaptation principles, fusion AT supports a myriad of learning paradigms, notably unsupervised learning, supervised learning, and reinforcement learning. In addition, domain knowledge in the form of symbolic rules can be inserted into fusion ART and subsequently refined as part of the network’s dynamics, which maximizes exploitation of the existing knowledge while retaining the plasticity of exploring new solutions. Several case studies will be presented, illustrating how such self-adaptive knowledge-based systems may be used as autonomous players in first-person shooting games, Computer Generated Forces (CGF) in air combat simulation, and human-like avatars in virtual environment.

Biography:

Dr Ah-Hwee Tan received a Ph.D. in Cognitive and Neural Systems from Boston University, a Master of Science and a Bachelor of Science (First Class Honors) in Computer and Information Science from the National University of Singapore. He is currently an Associate Professor at the School of Computer Engineering (SCE), Nanyang Technological University and was the founding Director of Emerging Research Laboratory, a center for incubating new interdisciplinary research initiatives. Prior to joining NTU, he was a Research Manager at the A*STAR Institute for Infocomm Research (I2R), heading the Text Mining and Intelligent Agents research programmes. His current research interests include cognitive and neural systems, brain-inspired intelligent agents, machine learning, and text mining. Dr. Tan has published over 200 technical papers in major international journals and conferences of his fields, including 6 edited books. He holds two US patents, five Singapore patents, and has spearheaded several A*STAR projects in commercializing a suite of knowledge management and text mining software. He serves as Associate Editor/Editorial Board Member of several journals, including IEEE Access, IEEE Transactions on Neural Networks and Learning, IEEE Transactions on SMC Systems, and Applied Soft Computing. He is a Senior Member of IEEE and Vice Chair of IEEE ETTC Task Force on Towards Human-Like Intelligence.

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