RL.md

Reinforcement Learning and Dopamine

The rl.go file provides core infrastructure for dopamine neuromodulation and reinforcement learning, including the Rescorla-Wagner learning algorithm (RW) and Temporal Differences (TD) learning, and a minimal ClampDaLayer that can be used to send an arbitrary DA signal.

• neuromod.go has basic functions for sending neuromodulatory values such as DA.

• The RW and TD DA layers use the SendMods layer-level method to send the DA to other layers, at end of each cycle, after activation is updated. Thus, DA lags by 1 cycle, which typically should not be a problem.