Lecture
This lecture explores factored representations for planning, focusing on reducing complexity by modeling features separately. It covers real-life planning problems like airport ground-traffic control and state space explosion. Techniques such as logic-based representations and neural networks are discussed, along with policy iteration and value function factoring. The lecture also delves into Graphplan, situation calculus, and least commitment planning, showcasing how these methods can improve planning efficiency.