RLPark 1.0.0
Reinforcement Learning Framework in Java

ControlPolicyAdapter.java

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00001 package rlpark.plugin.rltoys.algorithms.control.acting;
00002 
00003 import rlpark.plugin.rltoys.envio.actions.Action;
00004 import rlpark.plugin.rltoys.envio.policy.Policies;
00005 import rlpark.plugin.rltoys.envio.policy.Policy;
00006 import rlpark.plugin.rltoys.math.vector.RealVector;
00007 
00008 public class ControlPolicyAdapter implements PolicyBasedControl {
00009   private static final long serialVersionUID = 7405967970830537947L;
00010   private final Policy policy;
00011 
00012   public ControlPolicyAdapter(Policy policy) {
00013     this.policy = policy;
00014   }
00015 
00016   @Override
00017   public Action step(RealVector x_t, Action a_t, RealVector x_tp1, double r_tp1) {
00018     return Policies.decide(policy, x_tp1);
00019   }
00020 
00021   @Override
00022   public Action proposeAction(RealVector x) {
00023     return Policies.decide(policy, x);
00024   }
00025 
00026   @Override
00027   public Policy policy() {
00028     return policy;
00029   }
00030 }
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