I'm trying to create a system that learns the Tower of Hanoi puzzle. The system I'm working off of uses a production system (similar to ACT-R), but uses hard-coded production rules. I know that Neil Taatgen's Primitive Information Processing Elements can be used to combine memory buffers/slots to run a task more efficiently, but is there some method of reinforcement learning that would guide the construction of sets of production rules in a cognitive system?Note that I've asked a similar question on the Computer Science StackExchange, but with more of a reinforcement learning perspective.
Reinforcement learning for combining production rules
reference request;cognitive modeling;reinforcement learning