Basic research on brain-inspired information processing systems with integrated computation for recognition and decision making

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This research aimed for the development of a new computational theory of the brain that integrates two types of brain's functionality, that is, recognition (input-related computation) and decision making (output-related computation). We also tried to establish a fundamental mathematical model based on the theory that may contribute to the realization of highly intelligent information processing systems like the brain.Specifically, we have modeled the computation associated with recognition and decision making as probabilistic inference on a dynamic Bayesian network model in a unified manner. We have also derived the exact solution of the probabilistic inference problem and proposed an approximation method for it.