Traps, Invariants, and Dead-Ends. Nir Lipovetzky, C. M. .
abstract   bibtex   
We consider the problem of deriving formulas that capture traps, invariants, and dead-ends in classical planning through polynomial forms of preprocessing. An invariant is a formula that is true in the initial state and in all reachable states. A trap is a conditional invariant: once a state is reached that makes the trap true, all the states that are reachable from it will satisfy the trap formula as well. Finally, dead-ends are formulas that are satisfied in states that make the goal unreachable. We introduce a preprocessing algorithm that computes traps in k-DNF form that is exponential in the k parameter, and show how the algorithm can be used to precompute invariants and dead-ends. We report also preliminary tests that illustrate the effectiveness of the preprocessing algorithm for identifying dead-end states, and compare it with the identification that follows from the use of the h1 and h2 heuristics that cannot be preprocessed, and must be computed at run time.
@inproceeduings {icaps16-201,
  track    = {Main Track},
  title    = {Traps, Invariants, and Dead-Ends},
  author   = {Nir Lipovetzky, Christian Muise, Hector Geffner},
  abstract = {We consider the problem of deriving formulas that capture traps, invariants, and dead-ends in classical planning through polynomial forms of preprocessing. An invariant is a formula that is true in the initial state and in all reachable states. A trap is a conditional invariant: once a state is reached that makes the trap true, all the states that are reachable from it will satisfy the trap formula as well. Finally, dead-ends are formulas that are satisfied in states that make the goal unreachable. We introduce a preprocessing algorithm that computes traps in k-DNF form that is exponential in the k parameter, and show how the algorithm can be used to precompute invariants and dead-ends. We report also preliminary tests that illustrate the effectiveness of the preprocessing algorithm for identifying dead-end states, and compare it with the identification that follows from the use of the h1 and h2 heuristics that cannot be preprocessed, and must be computed at run time.},
  keywords = {Classical planning,Model-based reasoning,Knowledge engineering for planning and scheduling}
}
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