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Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC
(Joint)		 2007-12-22
15:45		 Aichi   Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama (Tokyo Inst. of Tech.) NC2007-84		 Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past. A common approach i... [more] NC2007-84
pp.75-80
NC 2007-06-15
09:00		 Okinawa OIST Seaside House Off-policy least-squares temporal difference learning and its convergence guarantee in finite horizon prorblems
Takeshi Mori, Shin-ichi Maeda, Shin Ishii (NAIST) NC2007-14		 Recently-developed off-policy temporal difference (TD) learning with linear function approximation has attracted attenti... [more] NC2007-14
pp.35-40
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