source: src/main/java/uva/projectai/y2018/jasparon/RLBOA.java@ 89

Last change on this file since 89 was 67, checked in by Aron Hammond, 6 years ago

Added support for agents that learn via ReinforcementLearning, including an implementation of an agent that uses tabular Q-learning

File size: 786 bytes
Line 
1package uva.projectai.y2018.jasparon;
2
3import genius.core.events.MultipartyNegoActionEvent;
4import genius.core.events.NegotiationEvent;
5import genius.core.listener.Listener;
6
7public interface RLBOA extends Listener<NegotiationEvent> {
8 /**
9 * This method should pass the reward and newState trough to its component
10 * that uses an RL-strategy
11 *
12 * @param reward
13 * @param newState
14 */
15 public void observeEnvironment(double reward, State newState);
16
17 /**
18 * This method should instantiate a new AbstractState object that represents
19 * a distinct state in the environment.
20 * @return
21 */
22 public AbstractState getStateRepresentation(MultipartyNegoActionEvent negoEvent);
23
24 public double getReward(MultipartyNegoActionEvent negoEvent);
25
26 public String instanceIdentifier();
27}
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