Jim Reggia
Professor Emeritus
2252 Iribe Center
(301) 405-2686
(301) 405-6707
Education:
Ph.D., University of Maryland (Computer Science)
Biography:
Jim Reggia is a professor emeritus of computer science in the University of Maryland Institute for Advanced Computer Studies.
His research covers neural computation, artificial intelligence, genetic programming, and artificial life. Reggia has developed methods for creating integrated neuro-computational systems, focusing on modeling cortical regions for visual and language processing, as well as mechanisms like self-organizing maps and working memory.
Go here to view Reggia‘s academic publications.
Publications
2010
2010. Parsimonious rule generation for a nature-inspired approach to self-assembly. ACM Transactions on Autonomous and Adaptive Systems (TAAS). 5(3):1-24.
2010. Self-assembly of neural networks viewed as swarm intelligence. Swarm Intelligence. 4(1):1-36.
2009
2009. An unsupervised learning method for representing simple sentences. Neural Networks, 2009. IJCNN 2009. International Joint Conference on. :2133-2140.
2009. A cooperative combinatorial Particle Swarm Optimization algorithm for side-chain packing. IEEE Swarm Intelligence Symposium, 2009. SIS '09. :22-29.
2009. Improving rule extraction from neural networks by modifying hidden layer representations. Neural Networks, 2009. IJCNN 2009. International Joint Conference on. :1316-1321.
2009. An oscillatory hebbian network model of short-term memory. Neural computation. 21(3):741-761.
2009. Running memory span: A comparison of behavioral capacity limits with those of an attractor neural network. Cognitive Systems Research. 10(2):161-171.
2009. A distributed learning algorithm for particle systems. Integrated Computer-Aided Engineering. 16(1):1-20.
2008
2008. Automated design of distributed control rules for the self-assembly of prespecified artificial structures. Robotics and Autonomous Systems. 56(4):334-359.
2007
2007. Swarm Intelligence Systems Using Guided Self-Organization for Collective Problem Solving. Advances in Complex Systems. 10(1):5-34.
2007. Swarm Intelligence Systems Using Guided Self-Organization for Collective Problem Solving. Advances in Complex Systems. 10(1):5-34.
2007. Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits. Neuroimage. 34(3):1093-1107.
2006
2006. Development of a Large-Scale Integrated Neurocognitive Architecture Part 1: Conceptual Framework. UMIACS-TR-2006-33
2006. Stigmergic self-assembly of prespecified artificial structures in a constrained and continuous environment. Integrated Computer-Aided Engineering. 13(4):289-312.
2006. Evolutionary design of neural network architectures using a descriptive encoding language. Evolutionary Computation, IEEE Transactions on. 10(6):676-688.
2005
2005. Using aggregate motion in multi-agent teams to solve search and transport problems. Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE. :373-380.
2005. Diagnostic problem solving using swarm intelligence. Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE. :365-372.
2005. Collective-movement teams for cooperative problem solving. Integrated Computer-Aided Engineering. 12(3):217-235.
2005. Evolutionary discovery of arbitrary self-replicating structures. Computational Science–ICCS 2005. :404-411.
2005. Mirror symmetric topographic maps can arise from activity-dependent synaptic changes. Neural computation. 17(5):1059-1083.
2005. Evolving processing speed asymmetries and hemispheric interactions in a neural network model. Neurocomputing. 65:47-53.
2004
2004. A descriptive encoding language for evolving modular neural networks. Genetic and Evolutionary Computation–GECCO 2004. :519-530.
2004. Using distributed partial memories to improve self-organizing collective movements. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on. 34(4):1697-1707.
2004. Extending self-organizing particle systems to problem solving. Artificial Life. 10(4):379-395.
2004. Temporally asymmetric learning supports sequence processing in multi-winner self-organizing maps. Neural Computation. 16(3):535-561.
2003
2003. Cost minimization during simulated evolution of paired neural networks leads to asymmetries and specialization. Cognitive Systems Research. 4(4):365-383.
2002
2002. Predicting nearest agent distances in artificial worlds. Artificial life. 8(3):247-264.
2002. Effects of callosal lesions in a model of letter perception. Cognitive, Affective, & Behavioral Neuroscience. 2(1):37-37.
2001
2001. Cortical Spreading depression and the pathogenesis of brain disorders: a computational and neural network-based investigation. Neurological research. 23(5):447-456.
2001. Conditions enabling the emergence of inter-agent signalling in an artificial world. Artificial Life. 7(1):3-32.
2001. Learning word pronunciations using a recurrent neural network. Neural Networks, 2001. Proceedings. IJCNN'01. International Joint Conference on. 1:11-15.
2001. Evolving columnar circuitry for lateral cortical inhibition. Neural Networks, 2001. Proceedings. IJCNN'01. International Joint Conference on. 1:278-283.
2000
2000. A computational model of lateralization and asymmetries in cortical maps. Neural computation. 12(9):2037-2062.
2000. Cortical inhibition as explained by the competitive distribution hypothesis. Network models for control and processing. :31-62.
2000. The temporal correlation hypothesis for self-organizing feature maps. International Journal of Systems Science. 31(7):911-921.
2000. A SIMULATION ENVIRONMENT FOR EVOLVING MULTIAGENT COMMUNICATION. UMIACS-TR-2000-64
1999
1999. Lesion effects in a bihemispheric letter-identification model. Neural Networks, 1999. IJCNN'99. International Joint Conference on. 1:215-218.
1999. A neural network model of lateralization during letter identification. Journal of Cognitive Neuroscience. 11(2):167-181.
1999. Pathogenic mechanisms in ischemic damage: a computational study. Computers in biology and medicine. 29(1):39-59.
1999. Penumbral tissue damage following acute stroke: a computational investigation. Progress in brain research. 121:243-260.
1999. A model of lateralization and asymmetries in cortical maps. Neural Networks, 1999. IJCNN'99. International Joint Conference on. 1:121-124.
1999. Interhemispheric effects on map organization following simulated cortical lesions. Artificial intelligence in medicine. 17(1):59-85.
1998
1998. Cellular automata models of self-replicating systems. Advances in Computers. 47:141-183.
1998. Spreading depression in focal ischemia: A computational study. Journal of Cerebral Blood Flow & Metabolism. 18(9):998-1007.
1998. Computational Models for the Formation of Protocell Structures. Artificial Life. 4:61-77.
1998. Computational studies of lateralization of phoneme sequence generation. Neural Computation. 10(5):1277-1297.
1998. Problem solving during artificial selection of self-replicating loops* 1. Physica D: Nonlinear Phenomena. 115(3-4):293-312.
1998. Self-replicating structures: evolution, emergence, and computation. Artificial Life. 4(3):283-302.
1997
1997. Automatic discovery of self-replicating structures in cellular automata. Evolutionary Computation, IEEE Transactions on. 1(3):165-178.
1997. Emergence of self-replicating structures in cellular automata space. Physica D. 110:252-276.
1997. Computer models: A new approach to the investigation of disease. MD Computing. 14:160-168.
1997. A computational model of acute focal cortical lesions. Stroke. 28(1):101-101.
1996
1996. Learning activation rules for associative networks. Neural Networks, 1996., IEEE International Conference on. 1:365-370.
1996. Computational studies of synaptic alterations in Alzheimer’s disease. Neural modeling of brain and cognitive disorders. :63-87.
1996. Learning Activation Rules Rather Than Connection Weights. International journal of neural systems. 7(2):129-148.
1996. Alignment of coexisting cortical maps in a motor control model. Neural computation. 8(4):731-755.
1996. Effects of varying parameters on properties of self-organizing feature maps. Neural Processing Letters. 4(1):53-59.
1996. Pathogenesis of schizophrenic delusions and hallucinations: a neural model. Schizophrenia bulletin. 22(1):105-105.
1996. A neural model of positive schizophrenic symptoms. Schizophrenia Bulletin. 22(1):105-123.
1995
1995. Patterns of functional damage in neural network models of associative memory. Neural computation. 7(5):1105-1127.
1995. Discovery of self-replicating structures using a genetic algorithm. Evolutionary Computation, 1995., IEEE International Conference on. 2:678-683.
1995. A large-scale neural model linking local neuronal dynamics to positron emission tomography (PET) regional cerebral blood ffow (rCBF) data. Soc Neurosci Abstr. 21:1988-1988.
1995. Symmetries of natural and artificial neural networks. Symmetry: Culture and Science. 6:446-449.
1995. A neural model of delusions and hallucinations in schizophrenia. Advances in Neural Information Processing Systems. :149-156.
1995. A neural model of memory impairment in diffuse cerebral atrophy. The British Journal of Psychiatry. 166(1):19-19.