Brain Emotional Learning-Based Intelligent Controller for Multi-Agent Systems

May 18, 2018, Webb 1100

Luis Rodolfo Garcia

Texas A&M University - Corpus Christi, Electrical Engineering


The proliferation of autonomous robots evidence forthcoming environments where multiple autonomous systems (MAS) will be interacting with each other, as well as with human beings, to perform complex tasks at a level never imagined before. Conventional methods for improving MAS performance address very specific challenges, but not general problems. Learning-based controllers offer adaptability and robustness against uncertainties, however, the computational complexity of these solutions is often not practically feasible. These drawbacks limit the applicability and penalize the performance of current MAS control methods. Recently, cognitive scientists advocate that “a single occurrence of an emotionally significant situation is remembered far more vividly and for a longer period than a task, which is repeated frequently”. This highlights that emotional processing is able to develop an effect that sustained sensory input is not able to achieve. The idea of using emotional learning in control systems has been pointed out in Reinforcement Learning areas, where it is suggested that emotions play the role of reinforcement signals driving the need for cognition. In this talk, we discuss a descriptive and a mathematical model of emotion processing in the mammalian brain, which is then modified to develop a hierarchical feedback control for a MAS plant. Preliminary results show how the basic features of the emotional learning system in combination with the MAS controller can help to effectively control a group of robots in real-time, in presence of system uncertainties and agent malfunction.

Speaker's Bio

Luis Rodolfo Garcia Carrillo was born in Durango, Mexico in 1980. He received his B.Sc. in Electronic Engineering in 2003, and his M.Sc. in Electrical Engineering in 2007, both from the Instituto Tecnologico de La Laguna, in Coahuila, Mexico. He received his Ph.D. in Control Systems from the University of Technology of Compiegne, France, in 2011, where he was advised by Professor Rogelio Lozano. From 2012 to 2013, he was a postdoctoral researcher at the Center for Control, Dynamical Systems and Computation at the University of California, Santa Barbara, where he was working with Professor Joao Hespanha. He currently holds an Assistant Professor position with the Department of Electrical Engineering at Texas A&M University – Corpus Christi. His current research interests include multi-agent control systems, intelligent controllers, and vision-based control.