T3: Fuzzy Reinforcement Learning

Tutorial presenter: Hamid Berenjii

Description

Reinforcement Learning is an important learning technique for learning from interactions with the environment. It is claimed that all future intelligent systems must be able to learn from the environment and this Conference is a very proper setting for a tutorial on this topic. Fuzzy Reinforcement Learning (FRL) extends Reinforcement Learning and enables it to deal with Fuzzy Systems. In this tutorial, we will first discuss Reinforcement Learning and then the main ways that the future fuzzy systems can learn by RL to improve their performances. In particular, here is the outline of this tutorial:

  • Reinforcement Learning:
    • What is it?
    • Evaluative Feedback
    • Dynamic Programming
    • Monte Carlo Methods
    • Temporal Difference Learning
    • Generalization and Function Approximation
  • Fuzzy Reinforcement Learning:
    • Generalized Approximate Reasoning based Intelligent Control (GARIC)
    • Fuzzy Q-Learning
    • Actor Critic based Fuzzy Reinforcement Learning (ACFRL)
  • Case Studies:
    • Cart Pole Balancing
    • Wireless Battery Power Control
    • Internet Node distribution
The participants of this tutorial will be engineers and educators interested in developing future intelligent systems with real-time learning capabilities.

About the presenter

Dr. Hamid Berenji received his M.S. and Ph.D. in Systems Engineering from the University of Southern California in 1980 and 1986, respectively. Since 1986, he has been working for the NASA Ames Research Center. He is currently the Chief Scientist at the Intelligent Inference Systems Corp. in Moffett Field, CA. Dr. Berenji has published more than 120 articles in Journals or as book chapters or in refereed conference proceedings. He has been an associate editor for the IEEE Transactions on Neural Networks and an associate editor for the IEEE Transactions on Fuzzy Systems. He is currently an associate editor for IEEE Transactions on Systems, Man, and Cybernetics (Part B). Dr. Berenji has been the chairman of the IEEE Neural Networks Council Technical committee on Fuzzy Systems. In 1993, he was the co-chairman of the IEEE Neural Networks Conference in San Francisco. He has won several awards from NASA and he is an elected IEEE Fellow.