Institut de Robòtica i Informàtica Industrial

GenerateFigure7aData

PURPOSE ^

Generates the data for Figure 7-left.

SYNOPSIS ^

function GenerateFigure7aData(fname)

DESCRIPTION ^

   Generates the data for Figure 7-left.

   In this experiment we compute the time (in seconds) for the first 
   iteration of Perseus for a discretized version of the problem 
   described in Figure 1 with increasing number of states.
   This gives allow to compare the computational complexity of the discrete
   and the continuous versions of Perseus (compare the execution times
   here with those in Figure 5).

   Parameters:
     fname: file where to store the results.

   See also MakeFigure1, MakeFigure7.

CROSS-REFERENCE INFORMATION ^

This function calls:
  • size Returns the size of a policy.
  • DBelief Discrete belief constructor.
  • get Get for GBeliefs.
  • GetTest1Parameters The example on Figure 1.
  • get Get function for the GMixture object.
  • get Gaussian object get function.
  • get Get function for CS_CO_CA_POMDPs.
  • get Get function for CS_CO_DA_POMDPs.
  • get Get function for CS_CO_POMDPs.
  • get Get function for CS_DO_CA_POMDPs.
  • Discretize Discretizes the state space of the CS_DO_DA_POMDP.
  • get Get function for CS_DO_DA_POMDPs.
  • get Get function for CS_POMDPs.
  • get Get function for DS_CO_CA_POMDPs.
  • get Get function for DS_CO_DA_POMDPs.
  • get Get function for DS_DO_CA_POMDPs.
  • get Get function for DS_DO_DA_POMDPs.
  • POMDP POMDP constructor.
  • Perseus The Perseus point-based POMDP solver.
  • SampleBeliefs Samples a set of beliefs from a POMDP.
  • UniformDistribution Uniform distribution in the POMDP state space.
  • get Get functio for POMDPs.
  • Discretize Converts a continuous space into a discrete one.
  • UniformDistribution Uniform probability on a continuous space.
  • UniformDistribution Uniform probability on a discrete space.
This function is called by:

SOURCE CODE ^

0001 function GenerateFigure7aData(fname)
0002 %   Generates the data for Figure 7-left.
0003 %
0004 %   In this experiment we compute the time (in seconds) for the first
0005 %   iteration of Perseus for a discretized version of the problem
0006 %   described in Figure 1 with increasing number of states.
0007 %   This gives allow to compare the computational complexity of the discrete
0008 %   and the continuous versions of Perseus (compare the execution times
0009 %   here with those in Figure 5).
0010 %
0011 %   Parameters:
0012 %     fname: file where to store the results.
0013 %
0014 %   See also MakeFigure1, MakeFigure7.
0015 
0016    ns=100:100:1000;
0017    
0018    % Nothing to be modified beyond this point
0019    
0020    nns=size(ns,2);
0021 
0022    [POMDP P]=GetTest1Parameters;
0023    
0024    stopCriteria=@(n,t,vc)(n>1);
0025    
0026    nRep=5;
0027    
0028    tp=zeros(1,nns);
0029    k=1;
0030    for n=ns
0031      
0032      fprintf('Discretizing the POMDP with %u states\n',n);
0033      DPOMDP=Discretize(POMDP,n);
0034      
0035      start=DBelief(UniformDistribution(get(DPOMDP,'StateSpace')));
0036      
0037      fprintf('Sampling Beliefs\n');
0038      B=SampleBeliefs(DPOMDP,start,P.nBeliefs,P.dBelief,P.stepsXtrial,P.rMin,P.rMax);
0039      r=0;
0040      for s=1:nRep
0041        [V Val Alpha t]=Perseus(DPOMDP,B,stopCriteria);
0042        r=r+t(2);
0043      end
0044      tp(k)=r/nRep;
0045      k=k+1;
0046  
0047    end
0048    
0049    save(fname,'ns','tp');
0050


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