public interface ActionSelector
An action selection policy for a reinforcement-learning algorithm. The job of the action selector is to select from the available actions in a particular state in such a way as to balance exploitation against exploration.
See:
Sutton, R. S., Barto, A. G., 1998. Reinforcement Learning: An Introduction.
MIT Press.
Modifier and Type | Method and Description |
---|---|
int |
act(int state,
MDPLearner learner)
Choose an action according to the current state and the
current value estimates for each action.
|
int act(int state, MDPLearner learner)
state
- The current state of the MDP.learner
- The algorithm used to update the value estimates.Copyright © 2014. All rights reserved.