Trash Picker

Description: "Trash Picker" is a demonstration game designed to showcase the implementation of a Naive Bayes classifier for creating an AI that learns from human behavior. In this game, you control Luso, a robot tasked with picking up trash in a grid. The game can be played by a human or by an AI that has learned from observing human players.

Objective: The goal is to maximize your score by collecting as much trash as possible within a limited number of moves. Avoid penalties by making efficient moves and collecting trash effectively.

Controls:

Button	Action
W	Move Up
S	Move Down
A	Move Left
D	Move Right
E	Stay Still
R	Move Randomly

Important Note: To ensure the AI learns effectively, the human player needs to play several rounds first. This allows the AI to observe and record the player's actions, improving its decision-making process when it takes control.

Technical Focus: This game primarily serves to demonstrate the application of a Naive Bayes classifier to mimic human behavior in a grid-based environment. The AI observes and records the actions taken by the human player and uses this data to make decisions when it takes control.

Source Code: For more details on the implementation and to access the source code, visit our GitHub repository.

Enjoy the game and explore how AI can learn and adapt to human behavior!