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公开(公告)号：US20170147949A1
公开(公告)日：2017-05-25
申请号：US15425924
申请日：2017-02-06
Inventor： Eiji UCHIBE , Kenji DOYA
CPC classification number: G06N20/00 , G06K9/6297 , G06N7/005
Abstract: A method of inverse reinforcement learning for estimating reward and value functions of behaviors of a subject includes: acquiring data representing changes in state variables that define the behaviors of the subject; applying a modified Bellman equation given by Eq. (1) to the acquired data: r ( x ) + γ V ( y ) - V ( x ) = ln π ( y | x ) b ( y | x ) , ( 1 ) = ln π ( x , y ) b ( x , y ) - ln π ( x ) b ( x ) , ( 2 ) where r(x) and V(x) denote a reward function and a value function, respectively, at state x, and γ represents a discount factor, and b(y|x) and π(y|x) denote state transition probabilities before and after learning, respectively; estimating a logarithm of the density ratio π(x)/b(x) in Eq. (2); estimating r(x) and V(x) in Eq. (2) from the result of estimating a log of the density ratio π(x,y)/b(x,y); and outputting the estimated r(x) and V(x).
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公开(公告)号：US20170213151A1
公开(公告)日：2017-07-27
申请号：US15329690
申请日：2015-08-07
Inventor： Eiji UCHIBE , Kenji DOYA
Abstract: A method of inverse reinforcement learning for estimating cost and value functions of behaviors of a subject includes acquiring data representing changes in state variables that define the behaviors of the subject; applying a modified Bellman equation given by Eq. (1) to the acquired data: q(x)+gV(y)−V(x)=−1n{pi(y|x))/(p(y|x)} (1) where q(x) and V(x) denote a cost function and a value function, respectively, at state x, g represents a discount factor, and p(y|x) and pi(y|x) denote state transition probabilities before and after learning, respectively; estimating a density ratio pi(y|x)/p(y|x) in Eq. (1); estimating q(x) and V(x) in Eq. (1) using the least square method in accordance with the estimated density ratio pi(y|x)/p(y|x), and outputting the estimated q(x) and V(x).
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