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Download Statistical Reinforcement Learning: Modern Machine Learning by Masashi Sugiyama PDF

By Masashi Sugiyama

Reinforcement studying (RL) is a framework for choice making in unknown environments in line with a large number of information. numerous sensible RL functions for company intelligence, plant regulate, and online game gamers were effectively explored lately. delivering an obtainable advent to the sector, this e-book covers model-based and model-free methods, coverage new release, and coverage seek tools. It offers illustrative examples and cutting-edge effects, together with dimensionality relief in RL and risk-sensitive RLm. The publication offers a bridge among RL and information mining and computing device studying examine.

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Additional resources for Statistical Reinforcement Learning: Modern Machine Learning Approaches

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Thus, the reward specifies the goal location. Thus, a policy also specifies a trajectory, which is a series of states and actions that the robot agent takes from a start state to an end state.

Thus, knowing the transitions means knowing the map of the maze. Thus, the reward specifies the goal location. Thus, a policy also specifies a trajectory, which is a series of states and actions that the robot agent takes from a start state to an end state.

Thus, the reward specifies the goal location. Thus, a policy also specifies a trajectory, which is a series of states and actions that the robot agent takes from a start state to an end state.

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