EXPERIENCE ENHANCEMENT TYPE ENHANCED LEARNING METHOD USING BEHAVIOR SELECTION NETWORK AND RECORD MEDIUM RECORDED WITH EXPERIENCE ENHANCEMENT TYPE ENHANCED LEARNING PROGRAM

摘要

PROBLEM TO BE SOLVED: To perform learning that has flexibility and to perform learning in the shortest path by changing the attenuation factor of enhancement value with the existence of experience that attenuates an episode and finishing active propagation when the enhancement value falls below prescribed threshold. SOLUTION: When an enhancement value is propagated from an adjacent storage module, a storage module voluntarily propagates the enhancement value to other storage modules it adjoins. A propagation method is to propagate storage modules which have experience that configures an episode and enhancement values R due to different attenuation factors except them after attenuation is performs as a whole as shown in a diagram. Active propagation is finished when enhancement value to be propagated falls below certain threshold. Learning in an L-ANA is to store how many enhancement values are propagated to each storage module. This active propagation can easily operate its characteristic with two parameters which are the dimension of enhancement value that is used at the time of performing active propagation and an attenuation factor that is used at the time of propagating.