Football Table RL

Reinforcement Learning

The football table employs on-line value iteration, namely Greedy-GQ $[math]\displaystyle{ (\lambda) }[/math]$ and Approximate-Q $[math]\displaystyle{ (\lambda) }[/math]$ . This page does not explain Reinforcement learning theory, it just touches on the usage and implementation of the provided library (libvfa located on the SVN). Too get a basic understanding of Reinforcement Learning i suggest reading the book by Sutton & Barto ^[1]. For more on using function approximation, i suggest the book by Lucian Busoniu et al. ^[2], which is freely available as e-book from within the TU/e network.

↑ Reinforcement Learning: an introduction, http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html
↑ Reinforcement Learning and Dynamic Programming using Function Approximation,http://www.crcnetbase.com/isbn/9781439821091

Value Function Approximation

[1] Reinforcement Learning: an introduction, http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html

[2] Reinforcement Learning and Dynamic Programming using Function Approximation,http://www.crcnetbase.com/isbn/9781439821091

[1]

[2]

Football Table RL

Reinforcement Learning

Value Function Approximation

Navigation menu

Search