AI engineering glossary · Reinforcement learning
What is stochastic policy?
Stochastic policy: A decision rule that gives a probability for each possible choice in a situation and samples from it. The randomness gives built-in exploration and can be optimal when the situation is only partly observed or when opponents must be kept guessing.
Stochastic policy: an example
In rock-paper-scissors, playing each option with probability 1/3 is the best stochastic rule against an unknown opponent.
Related terms
More Reinforcement learning terms
- Target network
- TD error
- TD(0)
- TD(lambda)
- Temporal-difference learning
- Terminal state
- Thompson sampling
- Transition probability
Where you learn it
Stochastic policy is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.