Training Agents 4: From reward functions to environments.

Description

Training Agents, Session 4: from reward functions to environments. In this live session, the reward stops being a function and becomes a place the agent acts in. In Session 3 the model answered once and a Python function scored it. Today the model runs a loop: open a file, run a…