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After nearly 11 years, I’ve finally decided to pull the plug on Usenet archive:

The page you have requested no longer exists!

But don’t panic just yet!

I’ve coded this page in a way, that it’s monitoring each redirect & capturing data about the thread you’ve requested. Page you’ve requested is still available in Google’s Usenet Archive. You should be able to access it using following URL:

Reinforcement Learning..

Note: I can’t guarantee that all pages can be found in Google Groups, but over 90% of the content should be there. If not, try the resources below!

Reinforcement learning!Reinforcement learning is an area of machine learning inspired by behaviorist psychology , concerned with how software agent s ought to
Reinforcement! – In behavioral psychology , reinforcement is a consequence that will strengthen an regarding reinforcement in learning theory and believed
Machine learning! – Machine learning is a subfield of computer science (CS) and artificial Reinforcement learning differs from the supervised learning
Markov decision process! – MDPs are useful for studying a wide range of optimization problem s solved via dynamic programming and reinforcement learning .
Q-learning! – Q-learning is a model-free reinforcement learning technique. Specifically, Q-learning can be used to find an optimal action-selection

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