Post on 22-Dec-2015
transcript
Local Search Techniques for Temporal Planning in LPG
Paper by Gerevini, Serina, Saetti, Spinoni
Presented by Alex
Overview of Problem
• What problem are they solving?– Temporal planning (duh)– More specifically? What kinds of action
restrictions?
Overview of Techniques
• In general, what techniques do they use?– Local search, variation of Walksat– Mix of Graphplan and POP– Complicated heuristics
Outline
• Search Space
• Local search and heuristics– Search operators– Various cost metrics
• Experiments
And TA-graphs
• What is a TA-graph?– Triple (LA-graph, Time-assign’t, Ordering Cs)
• What do the time assignments represent?– Earliest time a fact can become true– Earliest time an action can finish executing
How does it fit into Graphplan?
• Only permanent action mutexes – meaning?
• What good are action mutexes in an LA-graph?
• How much of Graphplan is left?
POP & LPG
• POP• Threats
– Promotion
– Demotion
• Causal Link• Least Commitment
• LPG• Mutexes
– LA-graph ordering
• Action-Effect edge• Topological Sort (as
opposed to total order of LA-graph)
Solution State
• What constraints does a TA-graph have to obey to be a solution?– Logical constraints (are goals and action
preconditions satisfied)– Temporal/Ordering constraints
• Time assign’ts consistent with orderings
• Ordering constraints imply mutex actions don’t co-occur
Local Search: Operators
• Every search operator fixes an “inconsistency” in the partial plan– What kinds of inconsistencies are there?
• How do you fix inconsistencies?
Local Search: Walksat
• Proposition with k clauses and n variables – With probability p, pick a variable at random
from an unsatisfied clause and flip its value– With prob. 1-p, flip value of variable that
maximizes number of satisfied clauses
WalkPlan
• For a given inconsistency, if there is a move that increases plan quality, do it.
• Otherwise, – with probability p, pick a move at random– With probability 1-p, pick best move
• Do random restarts after too many moves
Questions about WalkPlan
• How do they pick the inconsistency to fix?
• Why do they change the Walksat algorithm?
• Where do they start search after a random restart?
Relaxed Plan
• When adding (or removing) action a, find relaxed plan for unsupported preconditions of a (or the preconditions that used to be supported by a, if removing a).
• In what way(s) is it relaxed?
Experiments
• Impressive, no?
• Are there any criticisms? caveats?– Is it fair to compare separately along the time
and quality axes? I.e., is a quickly-generated but very crappy plan better than a more slowly-generated but decent plan?