Dr. Guez's interests are in understanding and applying the principles of intelligent decision making, adaptation, optimization, and control demonstrated in biological, social and anthropomorphic systems in automation, robotics, business and other areas. His immediate research concerns the design and construction of real time, hierarchical control architecture for a multi-robotic system operating in a partially known environment, which is based upon competitive/cooperative behavior criteria. Some important subproblems of this project are control of high dimensional nonlinear systems, dynamic planning of productive robot paths among obstacles, heuristic based optimization, design of learning systems, and neuromorphic realization of variable structure adaptive controllers, multiple objectives, and optimization.
Dr. Guez has over 200 technical publications, book chapters and patents. He is a frequent consultant to international industry and government, having been a consultant to more than 50 companies and government organizations in business system optimization, decision making, and automation. He is a frequent reviewer for IEEE Trans. on System, Man Cybernetics, IEEE Trans. on Robotics and Automation, Journal ofNeural Networks, IEEE Control System Magazine, Journal of Intelligent and Robotic Systems, IEEE Computer, NSF, and Advanced Technology Center-Benjamin Franklin Partnership.
Additionally, he has over 30 years of experience in control systems, decision making & optimization in business systems, automation, biomedical systems and devices, neuroengineering, machine learning and adaptation.