Huddersfield

Flexible Planning Ian Miguel AI Group Department of Computer Science University of York

AI Planning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Example – Initial State ,[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 ,[object Object],[object Object],[object Object]

Example - Operators ,[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1

Example – Solution ,[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1

Example - Solution ,[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1

Example - Solution ,[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1

Example - Solution ,[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 guard 1 pkg 1 pkg 2

Solving Planning Problems ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Planning Graph ,[object Object],[object Object],[object Object],[object Object],Initial Conditions Actions 1 Propositions 1 . . . . . . . . . Goals

Mutual Exclusion Constraints ,[object Object],[object Object]

Mutual Exclusion Constraints ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Mutual Exclusion Constraints ,[object Object],[object Object],[object Object],[object Object],[object Object],a b

Finding a Valid Plan ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The Constraint Satisfaction Problem ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Specify allowed combinations of assignments of values to variables.

The CSP Viewpoint ,[object Object],[object Object],[object Object],[object Object],[object Object],Goal Sub-problem

Memoisation ,[object Object],[object Object],[object Object],[object Object],Goal Sub-problem

Memoset Propagation ,[object Object],[object Object],Goal Sub-problem

A Weakness of Classical Planning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Flexible Planning Problems ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Truth Degree ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Flexible Plan Quality ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Flexible Example ,[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 L={l  , l 1 , l 2 , l T }

Flexible Example ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 L={l  , l 1 , l 2 , l T }

Flexible Planning Graph ,[object Object],[object Object],[object Object],Actions 1 Propositions 1 . . . . . . . . . l 2 l 3 l 1

Finding Valid Flexible Plans: Flexible Graphplan ,[object Object],[object Object],[object Object],[object Object],Goal Sub-problem

Short Compromise Plan ,[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 L={l  , l 1 , l 2 , l T } 4-steps ( l 1 )

Longer Plan, Fewer Compromises ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 L={l  , l 1 , l 2 , l T } 6-steps ( l 2 )

Limited Graph Expansion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Satisfaction Degree Propagation ,[object Object],[object Object],[object Object],[object Object],l 1 Action1 Action2 Level a Level a+1

Satisfaction Degree Propagation ,[object Object],[object Object],l 1 Action1 Action3 Level a Level a+1 l 2 l 2

Satisfaction Degree Propagation ,[object Object],[object Object],l 1 Action1 Action3 Level a Level a+1 l 2 l 2 l 2

Results: FGP vs Boolean Solving ,[object Object]

Utility of Limited Graph Expansion/Satisfaction Propagation ,[object Object]

Flexible Graphplan: Observations ,[object Object],[object Object],[object Object],[object Object]

Drowning and Leximin Ordering ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Solution (Leximin) ,[object Object],[object Object],[object Object],[object Object],[object Object],c 1 c 2 c 4 c 3 r 1 r 2 r 3 m 1 m 2 pkg 1 pkg 2 guard 1 L={l  , l 1 , l 2 , l T } 5-steps ( l 1 , l 2 , l 2 , l 2 ) Also finds 2 more plans that FGP misses.

Finding Leximin-optimal Plans: Leximin FGP ,[object Object],[object Object],[object Object],[object Object],Goal Sub-problem

Enhancements ,[object Object],[object Object],[object Object],[object Object],{ l 1 , l 2 } Action1 Action3 Level a Level a+1 { l 2 , l 3 } { l 2 , l 3 } { l 1 }

Satisfaction Degree Vector Propagation ,[object Object],[object Object],[object Object],{ l 1 , l 2 } Action1 Action3 Level a Level a+1 { l 2 , l 3 } { l 2 , l 3 } { l 1 , l 2 , l 3 } Action2

Removing Duplicates ,[object Object],[object Object],[object Object],[object Object],[object Object],{ l 1 } Action1 Action2 Level a Level a+1 {?, l 3 } { l 1 } { l 1 }

Results: BBFGP vs. LFGP ,[object Object]

Results: Flexible Logistics ,[object Object],[object Object]

Utility of Satisfaction Degree Vector Propagation ,[object Object],[object Object],[object Object],[object Object],[object Object]

Leximin FGP: Observations ,[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusions ,[object Object],[object Object],[object Object],[object Object]

Related Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Future Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Acknowledgements ,[object Object],[object Object]

Resources ,[object Object],[object Object],[object Object],[object Object]

Huddersfield

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Ähnlich wie Huddersfield

Ähnlich wie Huddersfield (20)

Mehr von ahmad bassiouny

Mehr von ahmad bassiouny (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Huddersfield