Computer Science Research

Adaptation and Learning in Distributed Systems Using Neural Networks

The research objective of this project is to represent each subsystem by an artificial neural network (or a related learning agent), and study these multi-agent learning systems in the framework of large-scale systems. Some of the problems and issues discussed in this multi-agent systems are as follows:

1. dealing with the uncertainty concerning overall system state due to the geographically distributed nature of the agents
2. designing learning and adaptation algorithms for individual agents
3. designing methods for combining knowledge structures(or, models) of all agents.

Solution methods have been developed to address some of these problems in specific interconnection models of multiple learning agents.

Project Presented By

Mukhopadhyay, Snehasis

Position:	Associate Professor
Mail:
Phone:	317-274-9732
Url:	http://www.cs.iupui.edu/~smukhopa/

Education Details

Research Interests

Associate Professor Mukhopadhyay has served as an Associate Director of the Bioinformatics Program in the IU School of Informatics ? Indianapolis from 2000 to 2006, and currently conducts research in the areas of Intelligent Systems, Intelligent Control, Neural Networks, Multi-Agent Systems, and Biocomputing. Dr. Mukhopadhyay holds degrees from Jadavpur University, India and the Indian Institute of Science, India as well as Master of Science and Ph.D. (1994) degrees in electrical engineering from Yale University. He is a National Science Foundation CAREER Award recipient.