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gradient ascent fix

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This commit is contained in:
Kevin Dee
2026-01-11 17:52:21 -08:00
parent 103e8b391b
commit 40df9059e7
2 changed files with 3 additions and 3 deletions
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2
@agent/run.m
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@@ -30,7 +30,7 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
% Compute performance values on partition
if ii < 5
% Compute sensing performance
sensorValues = obj.sensorModel.sensorPerformance(obj.pos, obj.pan, obj.tilt, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
sensorValues = obj.sensorModel.sensorPerformance(pos, obj.pan, obj.tilt, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
% Objective performance does not change for 0, +/- X, Y steps.
% Those values are computed once before the loop and are only
% recomputed when +/- Z steps are applied

4
test/test_miSim.m
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@@ -31,8 +31,8 @@ classdef test_miSim < matlab.unittest.TestCase
objective = sensingObjective;
% Agents
minAgents = 4; % Minimum number of agents to be randomly generated
maxAgents = 6; % Maximum number of agents to be randomly generated
minAgents = 2; % Minimum number of agents to be randomly generated
maxAgents = 2; % Maximum number of agents to be randomly generated
sensingLength = 0.05; % length parameter used by sensing function
agents = cell(0, 1);