We present the first effective SAT heuristics for planning with expressive planning languages such as ADL. Recently, SAT heuristics for STRIPS planning have been introduced. In this work we show that the basic ideas in the heuristic can be gen-eralized to actions with conditional effects but without dis-junction, and that disjunction requires a more fundamental analysis of the STRIPS heuristic, which, despite complica-tions, will still lead to a natural heuristic which can be imple-mented efficiently. The experimental analysis shows substan-tial and systematic improvements over the state of the art in planning with SAT with ADL
This thesis deals with Artificial Intelligence planning. After introducing the domain and the main a...
In recent work we showed that planning problems can be efficiently solved by general propositional s...
TheBlackbox planning system unifies the planning as satisfiability framework (Kautz and Selman 1992,...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
We present an effective SAT encoding of planning with partial knowledge, tests, branches, and non-d...
In the planning-as-SAT paradigm there have been numerous recent developments towards improving the s...
Most of the key computational ideas in planning have been developed for simple planning languages wh...
AbstractPlanning as satisfiability is a very efficient technique for classical planning, i.e., for p...
We introduce a novel method for encoding cost optimal delete-free STRIPS Planning as SAT. Our method...
Abstract. In many types of planning algorithms distance heuristics play an important role. Most of t...
Planning as satisfiability is a very efficient technique for classical planning, i.e., for planning ...
In recent work we showed that planning prob-lems can be efficiently solved by general propo-sitional...
We study the relationship between optimal planning algorithms, in the form of (iterative deepening) ...
Recent work by Kautz et al. provides tantalizing evidence that large, classical planning problems ma...
A limitation of the SAT approach to planning and the more recent Weighted-SAT approach to planning w...
This thesis deals with Artificial Intelligence planning. After introducing the domain and the main a...
In recent work we showed that planning problems can be efficiently solved by general propositional s...
TheBlackbox planning system unifies the planning as satisfiability framework (Kautz and Selman 1992,...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
We present an effective SAT encoding of planning with partial knowledge, tests, branches, and non-d...
In the planning-as-SAT paradigm there have been numerous recent developments towards improving the s...
Most of the key computational ideas in planning have been developed for simple planning languages wh...
AbstractPlanning as satisfiability is a very efficient technique for classical planning, i.e., for p...
We introduce a novel method for encoding cost optimal delete-free STRIPS Planning as SAT. Our method...
Abstract. In many types of planning algorithms distance heuristics play an important role. Most of t...
Planning as satisfiability is a very efficient technique for classical planning, i.e., for planning ...
In recent work we showed that planning prob-lems can be efficiently solved by general propo-sitional...
We study the relationship between optimal planning algorithms, in the form of (iterative deepening) ...
Recent work by Kautz et al. provides tantalizing evidence that large, classical planning problems ma...
A limitation of the SAT approach to planning and the more recent Weighted-SAT approach to planning w...
This thesis deals with Artificial Intelligence planning. After introducing the domain and the main a...
In recent work we showed that planning problems can be efficiently solved by general propositional s...
TheBlackbox planning system unifies the planning as satisfiability framework (Kautz and Selman 1992,...