RLPark 1.0.0
Reinforcement Learning Framework in Java
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00001 package rlpark.plugin.rltoys.algorithms.representations.discretizer.partitions; 00002 00003 import rlpark.plugin.rltoys.algorithms.representations.discretizer.partitions.AbstractPartitionFactory.AbstractPartition; 00004 00005 class BoundedPartition extends AbstractPartition { 00006 private static final long serialVersionUID = 237927027724145937L; 00007 00008 public BoundedPartition(double min, double max, int resolution) { 00009 super(min, max, resolution); 00010 } 00011 00012 @Override 00013 public int discretize(double input) { 00014 double margin = intervalWidth * .0001; 00015 double boundedInput = Math.min(Math.max(input, min + margin), max - margin); 00016 int result = (int) ((boundedInput - min) / intervalWidth); 00017 assert result >= 0 && result < resolution; 00018 return result; 00019 } 00020 }