Chicken Invaders is a retro game most of us played in the early 2000's. The game plays a huge part in our memories and was groundbreaking at the time, but how about we try to make an agent play instead of a human player?
This project uses informed searching algorithms like BFS, DFS, UCS and more as well as uninformed searching such as genetic, simulated annealing, and more to find the best order of decisions to play the game.
In addition, it uses reinforcement learning (Q-learning) to find the best set of decisions to play the game.
Note: the enviroment is re-constructed from the original game to fit all the search algorithms.