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University

Elementary Reinforcement Learning and Reinforcement Learning in Practice

Slides, videos

University College London

David Silver

Information

Scientific Literature

Statistical Markov model in which the system being modeled is assumed to be a Markov process with hidden states.

Information

Wikipedia

Mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker; the discrete stochastic version of the optimal control problem

Education

Literature

present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning

Marco Wiering Martijn van Otterlo

Education

Literature

provide a clear and simple account of the key ideas and algorithms of reinforcement learning

Richard S. Sutton Andrew G. Barto

Information

Wikipedia

a model-free reinforcement learning algorithm; to learn a policy, which tells an agent what action to take under what circumstances

Application

Software

Open source interface to reinforcement learning tasks, different environments

Documentation, Github

OpenAI

Information

Wikipedia

methods comprise a class of algorithms for sampling from a probability distribution.

Education

Literature

Mathematical emphasis on RL

Csaba Szepesv´ari

Open source interface to reinforcement learning tasks, different environments

*Upvote*
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*

Elementary Reinforcement Learning and Reinforcement Learning in Practice

*Upvote*
*
*

present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning

*Upvote*
*
*

provide a clear and simple account of the key ideas and algorithms of reinforcement learning

*Upvote*
*
*

Mathematical emphasis on RL

*Upvote*
*
*

Statistical Markov model in which the system being modeled is assumed to be a Markov process with hidden states.

*Upvote*
*
*

Statistical Markov model in which the system being modeled is assumed to be a Markov process with hidden states.

*Upvote*
*
*

Mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker; the discrete stochastic version of the optimal control problem

*Upvote*
*
*

a model-free reinforcement learning algorithm; to learn a policy, which tells an agent what action to take under what circumstances

*Upvote*
*
*

methods comprise a class of algorithms for sampling from a probability distribution.

*Upvote*
*
*

Open source interface to reinforcement learning tasks, different environments

*Upvote*
*
*

Elementary Reinforcement Learning and Reinforcement Learning in Practice

*Upvote*
*
*

present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning

*Upvote*
*
*

provide a clear and simple account of the key ideas and algorithms of reinforcement learning

*Upvote*
*
*

Mathematical emphasis on RL

*Upvote*
*
*

Reinforcement Learning