Towards compositional automated planning
Paper i proceeding, 2020

The development of efficient propositional satisfi-
ability problem solving algorithms (SAT solvers) in the past
two decades has made automated planning using SAT-solvers
an established AI planning approach. Modern SAT solvers can
accommodate a wide variety of planning problems with a large
number of variables. However, fast computing of reasonably long
plans proves challenging for planning as satisfiability. In order
to address this challenge, we present a compositional approach
based on abstraction refinement that iteratively generates, solves
and composes partial solutions from a parameterized planning
problem. We show that this approach decomposes the monolithic
planning problem into smaller problems and thus significantly
speeds up plan calculation, at least for a class of tested planning
problems.

compositional planning

automated planning

intelligent automation

SAT solvers

abstraction refinement

artificial intelligence

planning as satisfiability

online planning

Författare

Endre Erös

Chalmers, Elektroteknik, System- och reglerteknik, Automation

Martin Dahl

Chalmers, Elektroteknik, System- och reglerteknik, Automation

Petter Falkman

Chalmers, Elektroteknik, System- och reglerteknik, Automation

Kristofer Bengtsson

Chalmers, Elektroteknik, System- och reglerteknik, Automation

IEEE International Conference on Emerging Technologies and Factory Automation, ETFA

25th IEEE ETFA
Vienna, Austria,

UNICORN - Sustainable, Peaceful and Efficient Robotic Refuse Handling

VINNOVA, 2017-10-25 -- 2020-08-31.

Virtuell beredning av operationer för fordonsunderhåll, UNIFICATION

VINNOVA, 2017-06-01 -- 2020-05-31.

Ämneskategorier

Reglerteknik

Datavetenskap (datalogi)

Mer information

Skapat

2020-09-13