Real-time sequentially decision for optimal action using prediction of the state-action pair

摘要

We previously reported that an approach to predict the changes of the state and action of the robot. In this paper, to extend this approach, we will attempt to apply the action to be taken in the future to current action. For the achievement of this point, firstly, we will attempt to apply the action to be taken in the future, to the current action, by extending the former approach. We will apply the prediction of the State-Action Pair that has former proposed method. This method predicts the robot state and action for the distant future, using the state that the robot adopt repeatedly. Accordingly, we will obtain the actions that the robot to be taken in the future. In addition, we consider the point that the state and the action of the robot will be changed continuously. In this paper, we propose the method that predicts the state and the action every time when the robot decide an action. By using this method, we will obtain the compensate current action. This paper presents the results of these studies and discusses methods that allow the robot decides its desirable behavior quickly, using the state predicted combined with optimal control method.