This paper presents a parametric system, devised and implemented to perform hierarchical planning by delegating the actual search to an external planner (the "parameter") at any level of abstraction, including the ground one. Aimed at giving a better insight of whether or not the exploitation of abstract spaces can be used for solving complex planning problems, comparisons have been made between instances of the hierarchical planner and their non hierarchical counterparts. To improve the significance of the results, three different planners have been selected and used while performing experiments. To facilitate the setting of experimental environments, a novel semi-automatic technique, used to generate abstraction hierarchies...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
It is well-known that state abstraction can speed up planning exponentially, under ideal condi tions...
The use of abstraction in problem solving is an effective approach to reducing search, but finding g...
Abstraction can be an effective technique for dealing with the complexity of planning tasks. This p...
We present a novel method for building style abstraction hierarchies in planning. The aim of this m...
AbstractWe present a novel method for building Abstrips style abstraction hierarchies in planning. T...
This paper addresses the problem of how to implement a proactive behavior according to a two-tiered...
We present a novel method for building ABSTRIPS-style abstraction hierarchies in planning. The aim o...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. A...
Planning will be an essential part of future autonomous robots and integrated intelligent systems. T...
Despite major progress in AI planning over the last few years, many interesting domains remain chall...
Ph.D. Thesis, Computer Science Dept., U. Rochester; Prof. Dana H. Ballard, thesis advisor; simultane...
A quantitative model of abstraction in problem solving is presented which explains how and to what e...
Complex problem solving can be substantially improved by the reuse of experience from previously sol...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
It is well-known that state abstraction can speed up planning exponentially, under ideal condi tions...
The use of abstraction in problem solving is an effective approach to reducing search, but finding g...
Abstraction can be an effective technique for dealing with the complexity of planning tasks. This p...
We present a novel method for building style abstraction hierarchies in planning. The aim of this m...
AbstractWe present a novel method for building Abstrips style abstraction hierarchies in planning. T...
This paper addresses the problem of how to implement a proactive behavior according to a two-tiered...
We present a novel method for building ABSTRIPS-style abstraction hierarchies in planning. The aim o...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. A...
Planning will be an essential part of future autonomous robots and integrated intelligent systems. T...
Despite major progress in AI planning over the last few years, many interesting domains remain chall...
Ph.D. Thesis, Computer Science Dept., U. Rochester; Prof. Dana H. Ballard, thesis advisor; simultane...
A quantitative model of abstraction in problem solving is presented which explains how and to what e...
Complex problem solving can be substantially improved by the reuse of experience from previously sol...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
Abstraction is one of the most promising approaches to improve the performance of problem solvers. I...
It is well-known that state abstraction can speed up planning exponentially, under ideal condi tions...