[02286] Partially Observable Stochastic Control with Memory Limitation and Mean-Field Approach
Session Time & Room : 1E (Aug.21, 17:40-19:20) @F401
Type : Contributed Talk
Abstract : In this presentation, we describe the difficulties with partially observable stochastic control, POSC, and then propose memory-limited POSC, ML-POSC, to solve them. POSC does not consider memory limitation, which hampers the applications to actual controllers. Furthermore, POSC needs to solve a functional differential equation, which is intractable even numerically. In contrast, ML-POSC explicitly formulates limited memories of controllers. Additionally, ML-POSC reduces a functional differential equation to a partial differential equation by the mean-field control technique.
