Q强化学习matlab源代码

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Q learning of single agent move in N rooms 
% Matlab Code companion of 
% Q Learning by Example
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
function q=ReinforcementLearning
clc;
format short
format compact

    % Two input: R and gamma
    % immediate reward matrix; 
    % row and column = states; -Inf = no door between room
    R=[-inf-inf-inf-inf   0 -inf;
       -inf-inf-inf   0-inf 100;
       -inf-inf-inf   0-inf -inf;
       -inf   0   0-inf   0 -inf;
          0-inf-inf   0-inf 100;
       -inf   0-inf-inf   0 100];

    gamma=0.80;            % learning parameter

    q=zeros（size（R））;      % initialize Q as zeroq的行数和列数等于矩阵R的。
    q1=ones（size（R））*inf;  % initialize previo