RLPark 1.0.0
Reinforcement Learning Framework in Java
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00001 package rlpark.example.irobot.surprise; 00002 00003 import rlpark.plugin.rltoys.algorithms.functions.states.AgentState; 00004 import rlpark.plugin.rltoys.envio.actions.Action; 00005 import rlpark.plugin.rltoys.envio.observations.Observation; 00006 import rlpark.plugin.rltoys.math.vector.RealVector; 00007 import rlpark.plugin.rltoys.math.vector.implementations.PVector; 00008 00009 public class RobotState implements AgentState { 00010 private static final long serialVersionUID = 6644415896368916415L; 00011 00012 @Override 00013 public RealVector update(Action a_t, Observation o_tp1) { 00014 return new PVector(new double[] { 1.0 }); 00015 } 00016 00017 @Override 00018 public double stateNorm() { 00019 return 1; 00020 } 00021 00022 @Override 00023 public int stateSize() { 00024 return 1; 00025 } 00026 }