James Reggia
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Professor 301/405-2686 TEL |
Research Interests
neural computation, multi-agent artificial life systems, evolutionary computation, cellular automata models of self-replication, knowledge acquisition, abductive reasoning, Bayesian classification and networks, parsimonious covering theory.
Background Information
James Reggia received his PhD in Computer Science from the University of
Maryland in 1981. He is currently a Professor in the Department of Computer
Science with a joint appointment in the Institute for Advanced Computer
Studies (UMIACS).
His research interests span swarm intelligence, neural computation, AI,
genetic programming, and artificial life. In the area of swarm intelligence,
his work has focused on developing new methods for controlling collective
movements and problem solving, studying how individual agent memory abilities
influence collective problem solving, and applying swarm intelligence to
self-assembly tasks. Recent work in the area of neural computation has
focused on developing new learning methods for use in recurrent networks,
generating symbolic interpretations of what trained networks have learned,
and constructing large, brain-inspired models of cognitive control. This
past work has been funded by DARPA, ONR, NSF, NIH, NASA, and multiple
industry sources. He regularly teaches computer science courses in neural
computation, AI, machine learning, evolutionary computation, and artificial life.
Links
Neuroscience and Cognitive Science ProgramApplied Mathematics and Scientific Computation
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