Q-Function

Expected cumulative reward from a state or state-action pair.

Fundamental recursive relationship defining optimal value functions.

Optimizing policies directly via gradient ascent on expected reward.

Combines value estimation (critic) with policy learning (actor).

Learning from data generated by a different policy.

All possible configurations an agent may encounter.

Set of all actions available to the agent.

Strategy mapping states to actions.

Expected cumulative reward from a state or state-action pair.