Production system models of learning and development
Production system models of learning and development
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Neural network learning and expert systems
Neural network learning and expert systems
Memory and learning of sequential patterns by nonmonotone neural networks
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Systems and Computers in Japan
Neural-Symbolic Cognitive Reasoning
Neural-Symbolic Cognitive Reasoning
Symbols among the neurons: details of a connectionist inference architecture
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Model of the activity of hippocampal neurons based on the theory of selective desensitization
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
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A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed representations of information are processed by dynamical systems without using symbols. We present a method for such computing. We constructed an inference system using a nonmonotone neural network, which is a kind of recurrent neural network with continuous-time dynamics. This system deduces a conclusion according to state transitions of the network in which knowledge is embedded as trajectory attractors. It has the powerful ability of analogical reasoning without special treatment for exceptional knowledge. We also propose a method of linking different neurodynamical systems and show that two mutually interacting systems can process complex spatiotemporal patterns.