Model-Based Agent
Domain: Agent Architectures
🎯 Motivation
The agent maintains an internal model of the world and uses it to make better decisions than a reflex agent.
📋 Concrete Example
The agent tracks: ‘File A was modified at 2pm. Tests last passed at 1pm. So tests might fail now.’ It uses its world model to predict outcomes before acting.
🔗 Analogy
A chess player who thinks several moves ahead - they maintain a mental model of the board and predict what happens after each move. Model-based agents do this with their environment.