parameterized variable gradient ascent step size

@agent/agent.m

@@ -34,6 +34,11 @@ classdef agent
         plotCommsGeometry = true;
     end
 
+    properties (SetAccess = private, GetAccess = public)
+        initialStepSize = 0.2;
+        stepDecayRate = NaN;
+    end
+
     methods (Access = public)
         [obj] = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
         [obj] = run(obj, domain, partitioning, t, index, agents);

@agent/initialize.m

@@ -24,6 +24,7 @@ function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorMod
     obj.sensorModel = sensorModel;
     obj.label = label;
     obj.plotCommsGeometry = plotCommsGeometry;
+    obj.stepDecayRate = obj.initialStepSize / maxIter;
 
     % Initialize performance vector
     obj.performance = [0, NaN(1, maxIter), 0];

@agent/run.m

@@ -66,7 +66,7 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
     gradC = [(C_delta(2)-C_delta(3))/(2*delta), (C_delta(4)-C_delta(5))/(2*delta), (C_delta(6)-C_delta(7))/(2*delta)];
 
     % Compute scaling factor
-    targetRate = 0.2 - 0.0008 * timestepIndex; % slow down as you get closer
+    targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
     rateFactor = targetRate / norm(gradC);
 
     % Compute unconstrained next position