Emergence of symbolic behavior from brain like memory with dynamic attention
Neural Networks - Special issue on organisation of computation in brain-like systems
Mixed states on neural network with structural learning
Neural Networks
Learning Semantic Combinatoriality from the Interaction between Linguistic and Behavioral Processes
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Biometrics from gait using feature value method
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
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We previously proposed a memory system of motion patterns [4] using an assotiative memory model. It forms symbolic representations of motion patterns based on correlations by utilizing bifurcations of attractors depending on the parameter of activation nonmonotonicity. But the parameter had to be chosen appropreately to some degree by manual. We propose here a way to provide the paremeter with self-organizing dynamics along with the retrieval of the associative momory. Attractors of the parameter are discrete states representing the hierarchical correlations of the stored motion patterns.