STAN is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques to enhance its performance. STAN competed in the AIPS-98 planning competition where it compared well with the other competitors in terms of speed, finding solutions fastest to many of the problems posed. Although the domain analysis techniques STAN exploits are an important factor in its overall performance, we believe that the speed at which STAN solved the competition problems is largely due to the implementation of its plan graph. The implementation is based on two insights: that many of the graph construction operations can be implemented as bit-level logical operations on bit vectors, and that the graph should not be explicitly construct...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
In this paper we discuss and describe preliminary results of integrating two strands of planning res...
Stan is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
STAN is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
STAN is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
AbstractWe introduce a new approach to planning in STRIPS-like domains based on constructing and ana...
We introduce a new approach to planning in STRIPS-like domains based on con-structing and analyzing ...
We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a...
AbstractWe introduce a new approach to planning in STRIPS-like domains based on constructing and ana...
This work describes graphplan, satplan and real-time adaptive A* planning algorithms. Through implem...
Although the deep affinity between Graphplan's backward search, and the process of solving con...
This paper describes an extension of graphplan to a subset of ADL that allows conditional and univer...
Recent new planning paradigms, such as Graphplan and Satplan, have been shown to outperform more tra...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
In this paper we discuss and describe preliminary results of integrating two strands of planning res...
Stan is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
STAN is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
STAN is a Graphplan-based planner, so-called because it uses a variety of STate ANalysis techniques ...
AbstractWe introduce a new approach to planning in STRIPS-like domains based on constructing and ana...
We introduce a new approach to planning in STRIPS-like domains based on con-structing and analyzing ...
We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a...
AbstractWe introduce a new approach to planning in STRIPS-like domains based on constructing and ana...
This work describes graphplan, satplan and real-time adaptive A* planning algorithms. Through implem...
Although the deep affinity between Graphplan's backward search, and the process of solving con...
This paper describes an extension of graphplan to a subset of ADL that allows conditional and univer...
Recent new planning paradigms, such as Graphplan and Satplan, have been shown to outperform more tra...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited successfully b...
In this paper we discuss and describe preliminary results of integrating two strands of planning res...