1. Pat Langley Computational Learning Laboratory Center for the Study of Language and Information Stanford University, Stanford, CA http://cll.stanford.edu/~langley/ May 28, 2004 Computational Learning for Classification and Problem Solving

2. Definition of a Machine Learning System that improves task performance by acquiring knowledge based on partial task experience a software artifact

3. Elements of a Learning System experience/ environment knowledge learning method performance element

4. Elements of Classification Learning observed examples category descriptions learning mechanism classification mechanism

5. Five Paradigms for Classification Learning Rule Induction Decision-Tree Induction Case-Based Learning Neural Networks Probabilistic Learning

16. Learning for Problem Solving problem-solving experience problem-solving knowledge learning mechanism problem solver

17. Operators for the Blocks World (pickup (?x) (on ?x ?t) (table ?t) (clear ?x) (arm-empty) => (<add> (holding ?x)) (<delete> (on ?x ?t) (clear ?x) (arm-empty))) (unstack (?x ?y) (on ?x ?y) (block ?y) (clear ?x) (arm-empty) => (<add> (holding ?x) (clear ?y)) (<delete> (on ?x ?y) (clear ?x) (arm-empty))) (putdown (?x) (holding ?x) (table ?t) => (<add> (on ?x ?t) (arm-empty)) (<delete> (holding ?x))) (stack (?x ?y) (holding ?x) (block ?y) (clear ?y) (  ?x ?y) => (<add> (on ?x ?y) (arm-empty)) (<delete> (holding ?x) (clear ?y))) Most formulations of the blocks world assume four operators: Each operator has a name, arguments, preconditions, an add list, and a delete list.

18. State Space for the Blocks World

21. Labeled Operators on a Solution Path

22. Search-Control Rules for the Blocks World ((holding ?x) (table ?t) (goal (on ?x ?y)) (<not> (clear ?y)) => (putdown ?x)) ((holding ?x) (table ?t) (goal (on ?y ?x)) (goal (on ?z ?y)) => (putdown ?x)) ((holding ?x) (block ?y) (clear ?y) (  ?x ?y) (goal (on ?x ?y)) (on ?y ?z) (goal (on ?y ?z)) => (stack ?x ?y)) ((on ?x ?y) (block ?y) (clear ?x) (arm-empty) (on ?y ?z) (<not> (goal (on ?y ?z)) => (unstack ?x ?y)) ((on ?x ?y) (block ?y) (clear ?x) (arm-empty) (<not> (goal (on ?x ?y)) => (unstack ?x ?y)) Quinlan’s FOIL system induces a number of selection rules: Note that these rules are sensitive to the description of the goal.

24. A Means-Ends Problem-Solving Trace

26. Partitioning a Solution into Macro-Operators

29. Selected References Billman, D., Fisher, D., Gluck, M., Langley, P., & Pazzani, M. (1990). Computational models of category learning. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society (pp. 989-996). Cambridge, MA: Lawrence Erlbaum. Langley, P. (1995). Elements of machine learning . San Francisco: Morgan Kaufmann. Shavlik, J. W., & Dietterich, T. G. (Eds.). (1990). Readings in machine learning . San Francisco: Morgan Kaufmann. VanLehn, K. (1989). Problem solving and cognitive skill acquisition. In M. I. Posner (Ed.), Foundations of cognitive science . Cambridge, MA: MIT Press.

30. End of Presentation