Today, I spent some time working on the mechanism to facilitate training (https://github.com/silasray/aiexplore/commit/d32af871b95c0664097326aabc1e61e92272adb9). Spent some time thinking through how the current design will handle cycles. While it’s not great, it should be decent enough for now. I’m not super happy with the fact that max_steps means something different in resolve() than in reinforce(), but I didn’t want to get distracted trying to make the patterns match for now.

The idea is that after reaching a solution, it walks back from the solution to the input nodes to find the shortest paths, then reinforces those, either with a positive or negative value. I’m playing with some ideas in my head about how exactly to do the scoring and adjustments to the Synapse weights during the training/reinforce phase, but I think I’ll get more into that tomorrow.