RLPark 1.0.0
Reinforcement Learning Framework in Java
|
00001 package rlpark.plugin.rltoys.algorithms.control.acting; 00002 00003 import rlpark.plugin.rltoys.envio.actions.Action; 00004 import rlpark.plugin.rltoys.envio.policy.Policy; 00005 import rlpark.plugin.rltoys.math.vector.RealVector; 00006 00007 public class UnknownPolicy implements Policy { 00008 private static final long serialVersionUID = -4805473070123975706L; 00009 private final Policy policy; 00010 00011 public UnknownPolicy(Policy policy) { 00012 this.policy = policy; 00013 } 00014 00015 @Override 00016 public double pi(Action a) { 00017 return 1.0; 00018 } 00019 00020 @Override 00021 public Action sampleAction() { 00022 return policy.sampleAction(); 00023 } 00024 00025 @Override 00026 public void update(RealVector x) { 00027 policy.update(x); 00028 } 00029 }