Hi Edward,
There has definitely been a good deal of work on reinforcement learning in Nengo.
These papers are probably a good place to start, they talk about implementing a model of bandit learning, the simplest RL case.
http://compneuro.uwaterloo.ca/publications/bekolay2011.html
http://compneuro.uwaterloo.ca/publications/stewart2012a.html
These papers extend those ideas to full temporal-difference RL, as well as hierarchical reinforcement learning.
http://compneuro.uwaterloo.ca/publications/rasmussen2013b.html
http://compneuro.uwaterloo.ca/publications/Rasmussen2014b.html
http://compneuro.uwaterloo.ca/publications/Rasmussen2014c.html
If you want to see some code examples, check out https://github.com/tcstewar/nengo_learning_examples (learning2
, learning5
, and learning6
are all RL-related, in roughly increasing order of complexity).