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reimplemented gradient ascent as central finite differences method

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This commit is contained in:
Kevin Dee
2026-01-11 12:42:48 -08:00
parent c47b7229ba
commit ec202d7790
12 changed files with 101 additions and 176 deletions
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5
test/test_miSim.m
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@@ -456,13 +456,10 @@ classdef test_miSim < matlab.unittest.TestCase
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3], zeros(1,3), 0, 0, geometry1, sensor, 3, "", false);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1), true, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1));
% Run the simulation
tc.testClass = tc.testClass.run();
if isgraphics(tc.testClass.agents{1}.debugFig)
close(tc.testClass.agents{1}.debugFig);
end
% tc.verifyGreaterThan(tc.testClass.performance(end)/max(tc.testClass.performance), 0.99); % ends up very near a relative maximum
end