Used to model uncertainty by running the same simulation thousands of times with random inputs to see the range of possible outcomes. numpy.random or PyMC (for Bayesian modeling).
Use loops or vectorized NumPy functions to generate thousands of random scenarios and aggregate the results into a probability distribution. 3. Why Python for M&S? Modeling and simulation in Python
You can write a basic Monte Carlo simulation in five lines of code. Used to model uncertainty by running the same
You define an agent class with specific rules and a "space" (like a grid). Every step of the simulation, each agent observes its surroundings and acts according to its logic. Stochastic & Monte Carlo Simulation Modeling and simulation in Python