The agents.py module implements a number of standard reinforcement learning (RL) agents that
can be run on OpenAI gym environments.
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Monte Carlo Methods
- First-visit Monte Carlo updates (on-policy)
- Incremental weighted importance sampling (off-policy)
- Cross-entropy method (Mannor, Rubinstein, & Gat, 2003)
-
Temporal-Difference Methods
- SARSA (on-policy) (Rummery & Niranjan, 1994)
- Q-learning (off-policy) (Watkins, 1989)
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Model-Based Methods
- Dyna-Q/Dyna-Q+ with prioritized sweeping (Sutton, 1990; Moore & Atkeson, 1993)
