Wumpus World and Knowledge Representation
The Wumpus World is a classic artificial intelligence problem that demonstrates fundamental concepts in knowledge representation and reasoning. In this environment, an intelligent agent must navigate through a dangerous cave system using logical inference and knowledge representation to make informed decisions.
Key Components:
- Environment: A 4x4 grid world containing pits, a Wumpus monster, and gold. The agent must find the gold and escape while avoiding dangers.
- Percepts: The agent receives sensory information about its environment:
- Breeze: Indicates a pit in an adjacent cell
- Stench: Indicates the Wumpus monster is nearby
- Glitter: Indicates the presence of gold
- Knowledge Representation: The agent maintains a knowledge base that includes:
- Logical statements about the environment
- Inferred knowledge from percepts
- Safe and dangerous locations
- Potential locations of hazards
- Reasoning: The agent uses:
- Propositional logic to represent knowledge
- Inference rules to deduce new information
- Truth maintenance to update beliefs
- Decision-making based on current knowledge
This simulation demonstrates how an AI agent can use knowledge representation and reasoning to make intelligent decisions in an uncertain environment. The agent must balance exploration, safety, and goal-seeking behavior while maintaining and updating its knowledge base.