RLPark 1.0.0
Reinforcement Learning Framework in Java

OffPolicyEvaluation.java

Go to the documentation of this file.
00001 package rlpark.plugin.rltoys.experiments.parametersweep.offpolicy.evaluation;
00002 
00003 import java.io.Serializable;
00004 
00005 import rlpark.plugin.rltoys.agents.offpolicy.OffPolicyAgentEvaluable;
00006 import rlpark.plugin.rltoys.agents.representations.RepresentationFactory;
00007 import rlpark.plugin.rltoys.experiments.helpers.Runner;
00008 import rlpark.plugin.rltoys.experiments.parametersweep.interfaces.PerformanceEvaluator;
00009 import rlpark.plugin.rltoys.experiments.parametersweep.parameters.Parameters;
00010 import rlpark.plugin.rltoys.experiments.parametersweep.reinforcementlearning.OffPolicyProblemFactory;
00011 
00012 public interface OffPolicyEvaluation extends Serializable {
00013   PerformanceEvaluator connectEvaluator(int counter, Runner behaviourRunner, OffPolicyProblemFactory environmentFactory,
00014       RepresentationFactory projectorFactory, OffPolicyAgentEvaluable learningAgent, Parameters parameters);
00015 
00016   int nbRewardCheckpoint();
00017 }
 All Classes Namespaces Files Functions Variables Enumerations
Zephyr
RLPark