Means-Ends_Analysis

• If problems are well formed, means-ends analysis and problem reduction can work well
• Weak method (makes little use of knowledge)

State Spaces

• Initial state and goal state, the path along is a means of solving the problem

Means-Ends Analysis

• Positive steps reduce the difference between the current state and the goal state, think the a* algorithm
• Example of a universal AI method
• No guarantee of optimality, or even being able to solve the problem

Problem Reduction

• Decompose a hard problem into several smaller, easier problems

• Think about how recurrsive solutions work to solve problems

• In the block stacking example, decompose the final state into a series of "milestones" that are more likely to lead to a successful solution.

• Does not provide guarantees of success