发明名称 SELECTING REINFORCEMENT LEARNING ACTIONS USING GOALS AND OBSERVATIONS
摘要 Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reinforcement learning using goals and observations. One of the methods includes receiving an observation characterizing a current state of the environment; receiving a goal characterizing a target state from a set of target states of the environment; processing the observation using an observation neural network to generate a numeric representation of the observation; processing the goal using a goal neural network to generate a numeric representation of the goal; combining the numeric representation of the observation and the numeric representation of the goal to generate a combined representation; processing the combined representation using an action score neural network to generate a respective score for each action in the predetermined set of actions; and selecting the action to be performed using the respective scores for the actions in the predetermined set of actions.
申请公布号 US2016292568(A1) 申请公布日期 2016.10.06
申请号 US201615091840 申请日期 2016.04.06
申请人 Google Inc. 发明人 Schaul Tom;Horgan Daniel George;Gregor Karol;Silver David
分类号 G06N3/08;G06N99/00 主分类号 G06N3/08
代理机构 代理人
主权项 1. A method for selecting an action to be performed by a reinforcement learning agent that interacts with an environment by receiving observations characterizing a current state of the environment and, in response, performing actions from a predetermined set of actions, wherein the method comprises: receiving an observation characterizing a current state of the environment; receiving a goal characterizing a target state from a set of target states of the environment; processing the observation using an observation neural network to generate a numeric representation of the observation; processing the goal using a goal neural network to generate a numeric representation of the goal; combining the numeric representation of the observation and the numeric representation of the goal to generate a combined representation; processing the combined representation using an action score neural network to generate a respective score for each action in the predetermined set of actions; and selecting the action to be performed using the respective scores for the actions in the predetermined set of actions.
地址 Mountain View CA US