Institut de Robòtica i Informàtica Industrial

MakeFigure9

PURPOSE ^

Generates Figure 9.

SYNOPSIS ^

function MakeFigure9

DESCRIPTION ^

   Generates Figure 9.

   This figure compare the average accumulate discounted reward obtained
   for the problem in Figure 1 when using actions sets with different size
   in the displacement (1, 2, and 4).

   This is an experiment to properly frame that in figure 10, when using
   continous action sets (i.e., when Perseus has to select the adequate
   displacement size in each case).

CROSS-REFERENCE INFORMATION ^

This function calls:
  • plot Plots a discrete belief.
  • plot Displays a particle-based belief.
  • GetTest1Parameters The example on Figure 1.
  • plot Plots a Gaussian mixture.
  • set Set method for Gaussian mixtures.
  • plot Plots a Gaussian.
  • GetData Loads and, if necessary, generates data from experiments.
  • TestRepWithStatistics Executes many times Perseus on a given problem and collects statistics.
  • plot Plots the CS_CO_ObsModel
  • POMDP POMDP constructor.
  • set Set function for PODMP (base type)
  • plot Plots the CS_CA_RewardModel
This function is called by:

SOURCE CODE ^

0001 function MakeFigure9
0002 %   Generates Figure 9.
0003 %
0004 %   This figure compare the average accumulate discounted reward obtained
0005 %   for the problem in Figure 1 when using actions sets with different size
0006 %   in the displacement (1, 2, and 4).
0007 %
0008 %   This is an experiment to properly frame that in figure 10, when using
0009 %   continous action sets (i.e., when Perseus has to select the adequate
0010 %   displacement size in each case).
0011 %
0012 
0013   h=clf;
0014   set(h,'name','C-POMDP Figure 9','numbertitle','off');
0015 
0016   fprintf('Loading/Generating the simulation results with normal parameters\n');
0017   GenData=@()(TestRepWithStatistics('Test1','Figure2',1:10));
0018   ResultsNormal=GetData('Results/Test1-Figure2-results.mat',GenData);
0019   
0020   [POMDP P]=GetTest1Parameters(4,9,1);
0021   GenData=@()(TestRepWithStatistics(POMDP,P,'Figure9-a',1:10));
0022   ResultsA1=GetData('Results/Test1-Figure9-a-results.mat',GenData);
0023   
0024   [POMDP P]=GetTest1Parameters(4,9,4);
0025   GenData=@()(TestRepWithStatistics(POMDP,P,'Figure9-b',1:10));
0026   ResultsA4=GetData('Results/Test1-Figure9-b-results.mat',GenData);
0027 
0028   
0029   plot(ResultsA1.tics,ResultsA1.SM.R,'linestyle',':');
0030   hold on;
0031   plot(ResultsNormal.tics,ResultsNormal.SM.R);
0032   plot(ResultsA4.tics,ResultsA4.SM.R,'linestyle','--');
0033 
0034   
0035   legend('Action Set \pm 1','Action Set \pm 2','Action Set \pm 4');
0036   
0037   xlabel('time (s)');
0038   ylabel('Acc. Disc. Reward');


Institut de Robòtica i Informàtica Industrial

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