NSCS 344, Week 6

Assignment 6

*** Due date: Start of class in Week 7 ***

Part 1: Implement the Pure Expected Value Theory model (2 points)

Part 2: Plot the choice curve for the Pure EV theory model (2 points)

Y = [0.25:0.01:0.75];
for i = 1:length(Y)
[EV_safe(i), EV_risky(i), choice(i)] = EVtheory_survey(10, Y(i), 20);
end

Part 3: Implement the Noisy Expected Value Theory model (2 points)

Part 4: Plot the choice curves for Noisy Expected Value Theory (2 points)

Part 5: Compute the softmax choice curve and compare it with the Noisy Expected Value Theory choice curve (2 points)

Part 6: The four parameter "softmax" function (2 Extra Credit Points)

Plot the choice curve for this function ...
for the free parameters β (same as before and related to σ), θ (set it to 5 to start with), set to 0.05, and set to 0.1.
By messing around with the parameter values, or thinking carefully about the equation above, what do θ, and control on the choice curve? What cognitive processes could these parameters be capturing?