Abstract. In many types of planning algorithms distance heuristics play an important role. Most of the earlier works restrict to STRIPS operators, and their application to a more general language with disjunctivity and conditional effects first requires an exponential size reduction to STRIPS operators. I present direct formalizations of a number of distance heuristics for a general operator description language in a uniform way, avoiding the exponentiality inherent in earlier reductive approaches. The formalizations use formulae to represent the conditions under which operators have given effects. The exponentiality shows up in satisfiability tests with these formulae, but would appear to be a minor issue because of the small size of the f...
We present a general framework for studying heuristics for planning in the belief space. Earlier wo...
In recent years, heuristic search methods for classical planning have achieved remarkable results. T...
In recent years, heuristic search methods for classical plan-ning have achieved remarkable results. ...
AbstractThe automatic derivation of heuristic functions for guiding the search for plans is a fundam...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
The automatic derivation of heuristic functions for guiding the search for plans in large spaces is ...
Most of the key computational ideas in planning have been developed for simple planning languages wh...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
We study an approach to learning heuristics for planning do-mains from example solutions. There has ...
The hm (m = 1 ...) family of admissible heuristics for STRIPS planning with additive costs generalis...
State spaces in classical planning domains are usually quite large and can easily be extended to lar...
Classical planning is the problem of finding a sequence of actions for achieving a goal from an ini...
Many current heuristics for domain-independent planning, such as Bonet and Geffner’s additive heuris...
A limitation of the SAT approach to planning and the more recent Weighted-SAT approach to planning w...
We present a general framework for studying heuristics for planning in the belief space. Earlier wo...
In recent years, heuristic search methods for classical planning have achieved remarkable results. T...
In recent years, heuristic search methods for classical plan-ning have achieved remarkable results. ...
AbstractThe automatic derivation of heuristic functions for guiding the search for plans is a fundam...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
The automatic derivation of heuristic functions for guiding the search for plans in large spaces is ...
Most of the key computational ideas in planning have been developed for simple planning languages wh...
We present the first effective SAT heuristics for planning with expressive planning languages such a...
We study an approach to learning heuristics for planning do-mains from example solutions. There has ...
The hm (m = 1 ...) family of admissible heuristics for STRIPS planning with additive costs generalis...
State spaces in classical planning domains are usually quite large and can easily be extended to lar...
Classical planning is the problem of finding a sequence of actions for achieving a goal from an ini...
Many current heuristics for domain-independent planning, such as Bonet and Geffner’s additive heuris...
A limitation of the SAT approach to planning and the more recent Weighted-SAT approach to planning w...
We present a general framework for studying heuristics for planning in the belief space. Earlier wo...
In recent years, heuristic search methods for classical planning have achieved remarkable results. T...
In recent years, heuristic search methods for classical plan-ning have achieved remarkable results. ...