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(Classical) AI Planning
General-Purpose Planning: State & Goals ,[object Object],[object Object],A C B C B A Initial state Goals ( Ke Xu )
General-Purpose Planning: Operators ,[object Object],[object Object],[object Object],[object Object],[object Object],?y ?x ?y ?x … … No block on top of ?x transformation No block on top of ?y nor ?x On table
Planning: Search Space A C B A B C A C B C B A B A C B A C B C A C A B A C B B C A A B C A B C A B C ( Michael Moll )
Some Examples ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Which of the following problems can be modeled as AI planning problems?   Answer: ALL!
FSM vs AI Planning Neither is more powerful than the other one Planning Operators ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Patrol Fight Monster In Sight No Monster FSM: A resulting plan: Patrol patrolled Fight No Monster Monster in sight
But Planning Gives More Flexibility ,[object Object],If conditions in the state change making the current plan unfeasible: replan! reasoning knowledge Planning Operators ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Many potential plans: Patrol Fight Patrol Fight Patrol Fight Patrol Fight Patrol Fight …
But… Does Classical Planning Work for Games? ,[object Object]
General Purpose vs. Domain-Specific General purpose : symbolic descriptions of the problems and the domain.  The plan generation algorithm the same Domain Specific : The plan generation algorithm depends on the particular domain Advantage:  - opportunity to have clear semantics Disadvantage: - symbolic description requirement Advantage:  - can be very efficient Disadvantage: - lack of clear semantics - knowledge-engineering for plan generation Planning:  find a sequence of actions to achieve a goal
Classes of General-Purpose Planners General purpose planners can be classified according to the space where the search is performed: ,[object Object],[object Object],[object Object],[object Object],[object Object],We are going to discuss these forms
State- and Plan-Space Planning ,[object Object],(total order) ,[object Object],(partial-order, least-commitment) State of the world
Why Plan-Space Planning? ,[object Object],[object Object],[object Object],B A C C B A
Why Plan-Space Planning? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],A B C C B A C B A
Hierarchical (HTN) Planning Principle:  Complex tasks are decomposed into simpler tasks. The goal is to decompose all the tasks into  primitive  tasks, which define actions that change the world. alternative methods Travel from UMD to Lehigh University  Travel(UMD, Lehigh) Fly(National, L.V. International) Travel(L.V. Int’nal,Lehigh) Travel(UMD,National) Travel by car Enough money  for gasoline Roads are passable  Seats available  Travel by plane Enough money for air  fare available Taxi(UMD,UMD-Metro) Metro(UMD-Metro,National) Taxi(L.V. Int’nal,Lehigh)
Application to Computer Bridge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Not enough time to search the game tree ( Dana S.  Nau )
How to Reduce the Size of the Game Tree? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],( Dana S.  Nau )
Universal Classical Planning (UCP)   (Khambampati, 1997) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Plan-space partially instantiated steps, plus constraints add steps & constraints State-space
Abstract Example Initial state final state Initial plan: Plan-space refinement State-space refinement Plan-space refinement State-space refinement
Why “Classical”? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Classical Planning

  • 2.
  • 3.
  • 4. Planning: Search Space A C B A B C A C B C B A B A C B A C B C A C A B A C B B C A A B C A B C A B C ( Michael Moll )
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. General Purpose vs. Domain-Specific General purpose : symbolic descriptions of the problems and the domain. The plan generation algorithm the same Domain Specific : The plan generation algorithm depends on the particular domain Advantage: - opportunity to have clear semantics Disadvantage: - symbolic description requirement Advantage: - can be very efficient Disadvantage: - lack of clear semantics - knowledge-engineering for plan generation Planning: find a sequence of actions to achieve a goal
  • 10.
  • 11.
  • 12.
  • 13.
  • 14. Hierarchical (HTN) Planning Principle: Complex tasks are decomposed into simpler tasks. The goal is to decompose all the tasks into primitive tasks, which define actions that change the world. alternative methods Travel from UMD to Lehigh University Travel(UMD, Lehigh) Fly(National, L.V. International) Travel(L.V. Int’nal,Lehigh) Travel(UMD,National) Travel by car Enough money for gasoline Roads are passable Seats available Travel by plane Enough money for air fare available Taxi(UMD,UMD-Metro) Metro(UMD-Metro,National) Taxi(L.V. Int’nal,Lehigh)
  • 15.
  • 16.
  • 17.
  • 18. Abstract Example Initial state final state Initial plan: Plan-space refinement State-space refinement Plan-space refinement State-space refinement
  • 19.