Home /Research /Reinforcement learning in dynamic environment: abstraction of state-action space utilizing properties of the robot body and environment
LEARNING

Reinforcement learning in dynamic environment: abstraction of state-action space utilizing properties of the robot body and environment

Kazuyuki Ito, Yutaka Takeuchi

Year
2016
Citations
5

Keywords

Reinforcement learningComputer scienceRobotFlexibility (engineering)Action (physics)AbstractionRobot learningState spaceDegrees of freedom (physics and chemistry)Focus (optics)

Related papers

Browse all LEARNING papers