Potential Consequence of Interconnected Intervention against Systemic Risk (COVID-19) via a Model-Driven Network-Agent Dynamic

Table 4

Code example of the strategy dynamics (exploration).

for i in range (n):	# loop for every individual within the t loop
#-------------------------------------------------------
# exploration
#============
temp = B [:,1:3]	# a temporary variable to save strategies
R3 = np.random.random(size = [n, 2]) <= (0.5 pe)	# randomly choose a certain(%) with conditional
temp [R3] += np.random.normal (mu, sigma, size = [n,2])[R3]	# normally distributed increment
B [:,1:3 ] = temp	# update strategy values