Training Agents 4: From reward functions to environments.
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…
- 01.Training Agents, Session 4: from reward functions to environments
- 02.In this live session, the reward stops being a function and becomes a place the agent acts in
- 03.In Session 3 the model answered once and a Python function scored it
This material is provided as an extended analytical summary.
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