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Matlab/karma_nash_equilibrium/karma_nash_equilibrium.m

@@ -300,20 +300,25 @@
     % Store end results
     if ne_param.save
         file_str = ['karma_nash_equilibrium/results/k_bar_', num2str(param.k_bar, '%02d')];
-        if param.n_alpha == 1
-            if alpha > 0.99 && alpha < 1
-                alpha_str = num2str(alpha, '%.3f');
-            else
-                alpha_str = num2str(alpha, '%.2f');
+        if param.n_mu > 1
+            file_str = [file_str, '_w'];
+            for i_mu = 1 : param.n_mu
+                file_str = [file_str, '_', num2str(param.w_up_mu(i_mu), '%.2f')];
             end
-            file_str = [file_str, '_alpha_', alpha_str, '.mat'];
-        else
+        elseif param.n_alpha > 1
             file_str = [file_str, '_z'];
             for i_alpha = 1 : param.n_alpha
                 file_str = [file_str, '_', num2str(param.z_up_alpha(i_alpha), '%.2f')];
             end
-            file_str = [file_str, '.mat'];
+        else
+            if alpha > 0.99 && alpha < 1
+                alpha_str = num2str(alpha, '%.3f');
+            else
+                alpha_str = num2str(alpha, '%.2f');
+            end
+            file_str = [file_str, '_alpha_', alpha_str];
         end
+        file_str = [file_str, '.mat'];
         save(file_str);
     end
 

Matlab/karma_nash_equilibrium/load_ne_parameters.m

@@ -1,7 +1,7 @@
 function ne_param = load_ne_parameters(param)
 
 % Maximum karma level. Used as a starting point
-ne_param.k_max = 80;
+ne_param.k_max = 50;
 
 % Set of all karma values
 ne_param.K = (0 : ne_param.k_max).';

Matlab/karma_nash_equilibrium/ne_functions/plot_sw_pi.m

@@ -13,7 +13,7 @@ function plot_sw_pi(fg, position, colormap, sw_pi_down_u_k_up_m, U, K, M, k_ave)
             subplot(1, num_U, i_u);
             sw_pi_plot{i_u} = heatmap(K, M, pi_mat.', 'ColorbarVisible','off');
             sw_pi_plot{i_u}.YDisplayData = flipud(sw_pi_plot{i_u}.YDisplayData);
-            sw_pi_plot{i_u}.Title = ['k_{avg} = ', num2str(k_ave, '%02d'), ' SW policy for u = ', num2str(U(i_u))];
+            sw_pi_plot{i_u}.Title = ['k_{bar} = ', num2str(k_ave, '%02d'), ' SW policy for u = ', num2str(U(i_u))];
             sw_pi_plot{i_u}.XLabel = 'Karma';
             sw_pi_plot{i_u}.YLabel = 'Message';
             sw_pi_plot{i_u}.FontName = 'Ubuntu';
@@ -29,7 +29,7 @@ function plot_sw_pi(fg, position, colormap, sw_pi_down_u_k_up_m, U, K, M, k_ave)
             pi_mat = squeeze(sw_pi_down_u_k_up_m(i_u,:,:));
             pi_mat(pi_mat <= 1e-6) = nan;
             sw_pi_plot{i_u}.ColorData = pi_mat.';
-            sw_pi_plot{i_u}.Title = ['k_{avg} = ', num2str(k_ave, '%02d'), ' SW policy for u = ', num2str(U(i_u))];
+            sw_pi_plot{i_u}.Title = ['k_{bar} = ', num2str(k_ave, '%02d'), ' SW policy for u = ', num2str(U(i_u))];
         end
     end
 end

Matlab/karma_nash_equilibrium/ne_functions/write_d_csv.m

@@ -1,20 +1,19 @@
 % Wrtie stationary distribution to csv file
-function num_K = write_d_csv(d_up_u_k, U, K, s_tol, fileprefix)
-    num_U = length(U);
-    num_K = length(K);
-    s_up_k = sum(d_up_u_k).';
+function n_k = write_d_csv(d_up_mu_alpha_u_k, sigma_up_k, param, ne_param, sigma_tol, fileprefix)
+    n_k = ne_param.n_k;
+    K = ne_param.K;
 
     % Remove tail of distribution where there are too few agents
-    while s_up_k(num_K) < s_tol
-        num_K = num_K - 1;
+    while sigma_up_k(n_k) < sigma_tol
+        n_k = n_k - 1;
     end
-    if num_K == length(K)
-        K = [K; K(end)+1];
-        d_up_u_k = [d_up_u_k, zeros(num_U, 1)];
+    if n_k == length(K)
+        K(end+1) = K(end)+1;
+        d_up_mu_alpha_u_k(:,:,:,end+1) = 0;
     end
 
     % Header
-    header = ["u", "k", "k2", "P(k)"];
+    header = ["mu", "alpha", "u", "k", "k2", "P(k)"];
     filename = [fileprefix, '.csv'];
     fout = fopen(filename, 'w');
     for i = 1 : length(header) - 1
@@ -24,8 +23,14 @@
     fclose(fout);
 
     % Data
-    for i_u = 1 : num_U
-        data = [U(i_u) * ones(num_K + 1, 1), K(1:num_K+1), K(1:num_K+1) - 0.5, d_up_u_k(i_u,1:num_K+1).'];
-        dlmwrite(filename, data, '-append');
+    for i_mu = 1 : param.n_mu
+        MU = i_mu * ones(n_k + 1, 1);
+        for i_alpha = 1 : param.n_alpha
+            ALPHA = param.Alpha(i_alpha) * ones(n_k + 1, 1);
+            for i_u = 1 : param.n_u
+                data = [MU, ALPHA, param.U(i_u) * ones(n_k + 1, 1), K(1:n_k+1), K(1:n_k+1) - 0.5, squeeze(d_up_mu_alpha_u_k(i_mu,i_alpha,i_u,1:n_k+1))];
+                dlmwrite(filename, data, '-append');
+            end
+        end
     end
 end

Matlab/karma_nash_equilibrium/ne_functions/write_pi_csv.m

@@ -1,23 +1,26 @@
 % Write policy to csv file
-function num_K = write_pi_csv(pi_down_u_k_up_m, s_up_k, U, K, pi_tol, s_tol, fileprefix)
-    num_U = length(U);
-    num_K = length(K);
-
+function n_k = write_pi_csv(pi_down_mu_alpha_u_k_up_m, sigma_up_k, param, ne_param, pi_tol, sigma_tol, fileprefix)
+    n_k = ne_param.n_k;
+
     % Remove tail of distribution where there are too few agents
-    while s_up_k(num_K) < s_tol
-        num_K = num_K - 1;
+    while sigma_up_k(n_k) < sigma_tol
+        n_k = n_k - 1;
     end
 
     % Remove 'zero' values
-    pi_down_u_k_up_m(pi_down_u_k_up_m < pi_tol) = 0;
-    for i_u = 1 : num_U
-        for i_k = 1 : num_K
-            pi_down_u_k_up_m(i_u,i_k,1:num_K) = pi_down_u_k_up_m(i_u,i_k,1:num_K) / sum(pi_down_u_k_up_m(i_u,i_k,1:num_K));
+    pi_down_mu_alpha_u_k_up_m(pi_down_mu_alpha_u_k_up_m < pi_tol) = 0;
+    for i_mu = 1 : param.n_mu
+        for i_alpha = 1 : param.n_alpha
+            for i_u = 1 : param.n_u
+                for i_k = 1 : n_k
+                    pi_down_mu_alpha_u_k_up_m(i_mu,i_alpha,i_u,i_k,1:n_k) = pi_down_mu_alpha_u_k_up_m(i_mu,i_alpha,i_u,i_k,1:n_k) / sum(pi_down_mu_alpha_u_k_up_m(i_mu,i_alpha,i_u,i_k,1:n_k));
+                end
+            end
         end
     end
 
     % Header
-    header = ["u", "k", "k2", "b", "b2", "P(b)"];
+    header = ["mu", "alpha", "u", "k", "k2", "b", "b2", "P(b)"];
     filename = [fileprefix, '.csv'];
     fout = fopen(filename, 'w');
     for i = 1 : length(header) - 1
@@ -27,7 +30,7 @@
     fclose(fout);
 
     % Header for mean of policy
-    header_mean = ["u", "k", "b"];
+    header_mean = ["mu", "alpha", "u", "k", "b"];
     filename_mean = [fileprefix, '_mean.csv'];
     fout = fopen(filename_mean, 'w');
     for i = 1 : length(header_mean) - 1
@@ -37,23 +40,28 @@
     fclose(fout);
 
     % Data
-    for i_u = 1 : num_U
-        u = U(i_u);
-        for i_k = 1 : num_K + 1
-            k = i_k - 1;
-            for i_b = 1 : num_K + 1
-                b = i_b - 1;
-                if i_b <= i_k && i_k <= num_K
-                    line = [u, k, k - 0.5, b, b - 0.5, pi_down_u_k_up_m(i_u,i_k,i_b)];
-                else
-                    line = [u, k, k - 0.5, b, b - 0.5, 2];
-                end
-                dlmwrite(filename, line, '-append');
-            end
+    for i_mu = 1 : param.n_mu
+        for i_alpha = 1 : param.n_alpha
+            alpha = param.Alpha(i_alpha);
+            for i_u = 1 : param.n_u
+                u = param.U(i_u);
+                for i_k = 1 : n_k + 1
+                    k = i_k - 1;
+                    for i_b = 1 : n_k + 1
+                        b = i_b - 1;
+                        if i_b <= i_k && i_k <= n_k
+                            line = [i_mu, alpha, u, k, k - 0.5, b, b - 0.5, pi_down_mu_alpha_u_k_up_m(i_mu,i_alpha,i_u,i_k,i_b)];
+                        else
+                            line = [i_mu, alpha, u, k, k - 0.5, b, b - 0.5, 2];
+                        end
+                        dlmwrite(filename, line, '-append');
+                    end
 
-            if i_k <= num_K
-                line_mean = [U(i_u), K(i_k), dot(squeeze(pi_down_u_k_up_m(i_u,i_k,:)), K)];
-                dlmwrite(filename_mean, line_mean, '-append');
+                    if i_k <= n_k
+                        line_mean = [i_mu, alpha, u, k, dot(squeeze(pi_down_mu_alpha_u_k_up_m(i_mu,i_alpha,i_u,i_k,:)), ne_param.K)];
+                        dlmwrite(filename_mean, line_mean, '-append');
+                    end
+                end
             end
         end
     end

Matlab/karma_nash_equilibrium/ne_functions/write_sigma_csv.m

@@ -0,0 +1,36 @@
+% Wrtie stationary karma distribution to csv file
+function n_k = write_sigma_csv(sigma_down_mu_alpha_up_k, sigma_up_k, param, ne_param, sigma_tol, fileprefix)
+    n_k = ne_param.n_k;
+    K = ne_param.K;
+
+    % Remove tail of distribution where there are too few agents
+    while sigma_up_k(n_k) < sigma_tol
+        n_k = n_k - 1;
+    end
+    if n_k == length(K)
+        K(end+1) = K(end) + 1;
+        sigma_down_mu_alpha_up_k(:,:,end+1) = 0;
+    end
+
+    % Renormalize
+    sigma_down_mu_alpha_up_k = sigma_down_mu_alpha_up_k ./ sum(sigma_down_mu_alpha_up_k, 3);
+
+    % Header
+    header = ["mu", "alpha", "k", "k2", "P(k)"];
+    filename = [fileprefix, '.csv'];
+    fout = fopen(filename, 'w');
+    for i = 1 : length(header) - 1
+        fprintf(fout, '%s,', header(i));
+    end
+    fprintf(fout, '%s\n', header(end));
+    fclose(fout);
+
+    % Data
+    for i_mu = 1 : param.n_mu
+        MU = i_mu * ones(n_k + 1, 1);
+        for i_alpha = 1 : param.n_alpha
+            data = [MU, param.Alpha(i_alpha) * ones(n_k + 1, 1), K(1:n_k+1), K(1:n_k+1) - 0.5, squeeze(sigma_down_mu_alpha_up_k(i_mu,i_alpha,1:n_k+1))];
+            dlmwrite(filename, data, '-append');
+        end
+    end
+end