planning to learn, learning to plan

Lecture 3-1 CS251: Intro to AI/Lisp II

Planning to Learn, Learning to Plan


Announcements

• Quiz

• A Review of AI Planning Techniques

• Reading for next time: Cognitive model for planning

• Allegro for Windows

• Project deadline I


What is planning?

“Figuring out what to do next”

• Wumpus agent already does that with:– First-order logic– Resolution

• Shortcomings– Default values– Efficiency


Why do we need planners?


STRIPS Planning

• State space search– Just like the search we saw last quarter

• “It’s all in the operators”

• What does a STRIPS operator look like?


STRIPS Operators

Go(there)

At(here), Path(here, there)

At(there), At(here)


Planning Terminology I

• STRIPS ops – Action description– Precondition– Effect / Postconditions / Add & Delete

• Operator schemata

• When is operator o applicable in situation s?


Planning Terminology II

• The final frontier of planning: space– State (situation) space– Plan space

• Plan space is populated by __________

• Operators– Refine by eliminating plans from the set of

plans under consideration– Modify plans by messing with them


Planning in Plan Space

• NOAH planner (Sacerdoti 1975) was first partial-order planner

• In state space, solution is a path– Series of operators

• In plan space, series of plan transformations– Examples: Expand detail, adding ordering

constraints


Pruning the Search Space

• Cutting down the search space– Means-end analysis– Prioritize goals– Identify interactions– Parallelism

• Abstraction levels– Different approaches– Early: NOAH, ABSTRIPS (Sacerdoti 1973)


A Problem in Plan Space

• The goal: Getting milk, banana and a drill and heading home

• Actions:– Go: From here to there– Buy: We’ve got money

• Good things to know– Hardware stores sell drills– Supermarkets sell milk and bananas


Getting Started

• Start with an initial plan Start

Finish

At(Home) Sells(SM, Banana)

Sells(SM, Milk) Sells(HWS, Drill)

Have(Milk) Have(Banana)Have(Drill) At(Home)


Next Step

Start

Finish

At(s) Sells(s, Drill) At(s) Sells(s, Milk)

Have(Drill) Have(Milk) At(Home) Have(Banana)

Buy(Drill) Buy(Milk) Buy(Bananas)

At(s) Sells(s, Bananas)


What have we got?

• Protection– Need to have drill– Buy drill achieves Have(Drill)– If we mess with drill buying, then …– When doesn’t it matter?


And after that...

Start

Finish

At(HWS) Sells(HWS, Drill) At(SM) Sells(SM, Milk)

Have(Drill) Have(Milk) At(Home) Have(Banana)

Buy(Drill) Buy(Milk) Buy(Bananas)

At(SM) Sells(SM, Bananas)


What’s the problem?

• Need to:– Go from home to hardware store– Go from home to supermarket

• Pick one and then...


Interactive Problems

• Big red arrows are protected links

• Protected from … threats

• Change the ordering

• The problem in the abstract– Suppose S1 achieves c for S2

– Now S3 comes along and clobbers c


Project topics

• Planning– Build a planner from scratch: (AB)STRIPS,

NOAH– Explore current planners

• Robotics– Investigate reactive planning: write a series

of RAPs– “Build” a robot using subsumption


Project Topics II

• Perception– Explore audio perception– Write an object recognizer (Pepsi cans in

Wayne’s World)

• Machine learning– Look at data mining (name & email from

newsgroup sigs)


Project Topics III

• Uncertainty– Build a system that constructs Bayesian

networks– Look at HMMs in speech recognition

• Natural language– Write a story generator– Tell jokes

planning to learn, learning to plan

Documents