probability_based_game_simulation
Now that we have created all the necessary modules, you can run the simulation by executing the game_simulation.py script. This project covers the following concepts:
We use Bernoulli distribution for individual game outcomes and Binomial distribution for the overall game results. We also implement Poisson distribution for modeling rare events.
The calculate_conditional_probability function in probability_calculations.py calculates the probability of winning given a certain move.
The calculate_pdf and calculate_cdf functions in probability_calculations.py can be used to calculate probability density function and cumulative distribution function for given distributions.
We use lambda functions in the player_move function in game_setup.py to define different strategies.
The simulate_round function in game_setup.py uses map to apply moves to all players, and filter_winners uses filter to select winning moves.
To run the simulation:
Save each module in a separate .py file with the names mentioned in the artifacts. Make sure you have the required libraries installed (matplotlib, scipy, numpy). Run the game_simulation.py script.
