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[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.
  • Classification : 49N30, 49N80, 49K45, 93E20
  • Format : Talk at Waseda University
  • Author(s) :
    • Takehiro Tottori (The University of Tokyo)
    • Tetsuya J. Kobayashi (The University of Tokyo)