Grid world is a simple environment often used in the field of artificial intelligence and reinforcement learning for testing and developing algorithms. It consists of a grid of cells, where each cell represents a state in the environment. Agents can move around the grid and interact with the environment according to certain rules.
Typically, the grid world environment includes features such as walls, obstacles, rewards, and possibly hazards. The goal of an agent in a grid world environment is often to navigate from a starting position to a goal position while avoiding obstacles and maximizing rewards.
Examples:
- Cliff Walking
- Maze Navigation
- Frozen Lake