1. Planning Planning is a special case of reasoning We want to achieve some state of the world Typical example is robotics Many thanks to Robin Burke, University of Chicago, for many of these ideas: http://people.cs.uchicago.edu/~burke/cs250/lectures/lecture1107.html

2. Search vs. Planning

3. Example: Taking a Bath Goal: Take A Bath Initial State: Final State:

4. Operators Actions you take that affect state Examples: RemoveClothes PutOnClothes TurnOnWater TurnOffWater GetInTub GetOutOfTub Can use search to find the right combination of actions InsertPlug RemovePlug Scrub Lather PourShampoo PlayWithDuckie

5. Problems with Search Need a good heuristic – may not have one No direct sense of which operators are relevant to the problem Other constraints Don’t want solutions where we take off clothes and put them on again several times Search might find one There is a directionality to what we want to do Once the plug is in, we don't even want to consider removePlug Blind search doesn't let us make these distinctions

6. How does planning improve on search? Explicitly represent the goal and the way it is achieved using logic Make "important" decisions first and fill in the details later Take advantage of independence Puzzles are puzzles because subgoals are interlocking (cannot do each tile of 8-puzzle separately) The real world is more forgiving in many cases: taking off my clothes will not affect the state of the plug in the tub Allows divide and conquer strategies

7. STRIPS Planning STRIPS = STanford Research Institute Problem Solver one of the first planning systems one of the first formalisms considerably extended now, but still in use an entire subfield of planning is planning using the STRIPS representation good place to start

8. STRIPS Representation States: Conjunctions of predicates applied to constants Goals: Conjunctions of predicates applied to constants or simple variables

9. STRIPS Representation Actions: Get agent from one state to another Action description: What to do, e.g. forward, vacuum, etc. Precondition: what must be true to do action PlugIn(Tub) would be a precondition for a Fill(Tub) action Effect: what changes occur due to action Full(Tub) would be effect of Fill(Tub)

10. Action Example Precondition automatically refers to situation before, effects to situation after Negation = retraction Actions can have variables

11. Integrating Search Still going to need to do some seaching Could go forward from initial state Progressive High branching factor problem Backward from goal Regressive Typically goals are conjunctive, works much like backward chaining

12. The STRIPS Planner Start with a goal TakingBath(Robot) Need to know what conditions achieve this goal for backward chaining Each conjunct is called a sub-goal Need to achieve all subgoals Want to know steps on how you got there

13. Algorithm Start with goal See if achieved already If not, see if there’s some operator that can achieve it Unclothed(x) In KB, I have Clothed(Robot) Unclothed(Robot) is achieved with the plan Undress(Robot) If no such operator, try and decompose by backward chaining If unable to do so, fail and backtrack

14. Full Example Start with goal Unclothed(Robot) & Full(Tub) & In(Robot,Tub) & Plugged(Tub) Operator Undress(x): Precond: Clothed(x) Effect: Unclothed(x) & ~Clothed(x) So plan is, for starters, Undress(Robot) Remaining goals: Full(Tub) & In(Robot, Tub) & Plugged(Tub) Next subgoal: Full(Tub)

15. Example continued We have an operator Fill(x) Precond: Plugged(x) Effect: Full(x) & ~Empty(x) So backward chain over precondition Try operator Plug(x) Precond: Unplugged(x) Effect: Plugged(x) & ~Unplugged(x) So add it to plan: Undress(Robot), Plug(Tub)

16. Example continued Now that precondition of Fill satisfied, add to plan Plan: Undress(Robot), Plug(Tub), Fill(Tub) Remaining goals: In(Robot,Tub) & Plugged(Tub) Use operator GetIn(x,y) to get in tub Plan: Undress(Robot), Plug(Tub), Fill(Tub), GetIn(Robot,Tub) Remaining goals: Plugged(Tub) – it’s true

17. What’s the catch? Test the solution at the end: You may clobber a condition along the way E.g. You have to leave bathroom to fill tub (get dressed) Done by keeping track of threats Unclothed(Robot) is a precondition for final goal Do not allow an operator which inserts Clothed(Robot) between Undress(Robot) and goal

18. Actual algorithm Select subgoal state S need to resolve Choose operator c to resolve it Record link from previous state to final state