On Tue, Mar 13, 2012 at 6:37 AM, Shankar Satish <[email protected]> wrote:
> Do you think my proposal about implementing reinforcement-learning
> algorithms (subject line: "GSOC project idea: online learning algorithms")
> is something that is well suited for integration into scikit-learn? Do you
> think it makes more sense to start a new scikit focussed on reinforcement
> learning?

Just a couple of comments. There are some RL Python implementations,
e.g. PyBrain (http://pybrain.org/) and RL-Glue/RL-Library
(http://glue.rl-community.org/wiki/Main_Page). It seems that none of
these are being actively developed.

The nature of RL problems implies that the architecture of the code is
different than the "single script" approach used in scikit-learn. For
instance, in RL-Glue/RL-Library you run three independent programs
(the agent, environment and experiment programs) plus the RL-Glue
process. This approach is natural because it mimics the actual RL
problem, where the agent and the environment are two different
entities. Also, in the case of RL-Glue, you can combine environments
and agents written in different languages. I wonder how this different
architecture of RL would match with the scikit-learn ecosystem.

Alejandro.

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