Infomax Neural Networks for Real-Time Learning and Control

University Of California-San Diego, La Jolla CA

Investigators

Abstract

Proposal Number: 0622229 Proposal Title: Infomax Neural Networks for Real-Time Learning and Control PI Name: Movellan, Javier R. PI Institution: University of California-San Diego The objective of this project is to develop principled methods for solving Infomax Control problems, i.e., problems that require the control of active sensors so as to maximize the value of the information they gather. Intellectual Merits: Recent advances in stochastic optimal control, neural networks, and machine learning have made it possible to approach this problem in a principled manner. The proposed approach relies on three methodologies: (1) Mathematical modeling; (2) Empirical studies to evaluate the predictions made by the models; (3) Development and evaluation of robotic systems. Broader Impacts: Infomax control is a critical problem with applications to robotics, autonomous navigation, distributed control, automatic teaching systems, and national defense. For example, the approach can be applied to develop tutoring automatic tutoring systems that ask questions so as to optimize the material learned by the students. It can also be used to develop algorithms for data-mining large datasets so as to acquire the relevant information as quickly and efficiently as possible. It can also be used for developing robots that actively scan the environment gathering the information that is most important to achieve their current goals. Finally the approach will provide a mathematical foundation to help understand how the brain connects perception and action. In addition to the funding of graduate students, research and education activities will be developed in conjunction with the Engineering Course at the Preuss School in San Diego, a charter School for low-income student in grades 6-12. The proposed activities will serve as an example of an approach to introduce and teach the latest technological and scientific research in local middle and high-schools.