Heuristic search is a state-of-the-art approach to classical planning. Several heuristic families were developed over the years to automatically estimate goal distance information from problem descriptions. Orthogonally to the development of better heuristics, recent years have seen an increasing interest in symmetry-based state space pruning techniques that aim at reducing the search effort. However, little work has dealt with how the heuristics behave under symmetries. We investigate the symmetry properties of existing heuristics and reveal that many of them are invariant under symmetries
AbstractGeometrical symmetries are commonly exploited to improve the efficiency of search algorithms...
Since their introduction, symmetries have proven to be very powerful for the solution of different t...
Many planning problems contain collections of symmetric objects, actions and structures which render...
Heuristic search is a state-of-the-art approach to classical planning. Several heuristic families we...
In heuristic search planning, state-space symmetries are mostly ignored by both the search algorithm...
Searching for computational tools that can further push the boundary of satisficing planning, we sho...
Symmetries arise in planning in a variety of ways. This paper describes the ways that symmetry aises...
Symmetries provide the basis for well-established approaches to tackle the state explosion problem ...
Previous research in Artificial Intelligence has identified the possibility of simplifying planning ...
Symmetry-based state space pruning techniques have proved to greatly improve heuristic search based ...
Previous work in symmetry detection for planning has identified symmetries between domain objects an...
The exploitation of symmetry in combinatorial search has typically focused on using information abou...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited suc-cessfully ...
This thesis focuses on improving the process of automated planing through symmetry breaking. The aim...
State spaces in classical planning domains are usually quite large and can easily be extended to lar...
AbstractGeometrical symmetries are commonly exploited to improve the efficiency of search algorithms...
Since their introduction, symmetries have proven to be very powerful for the solution of different t...
Many planning problems contain collections of symmetric objects, actions and structures which render...
Heuristic search is a state-of-the-art approach to classical planning. Several heuristic families we...
In heuristic search planning, state-space symmetries are mostly ignored by both the search algorithm...
Searching for computational tools that can further push the boundary of satisficing planning, we sho...
Symmetries arise in planning in a variety of ways. This paper describes the ways that symmetry aises...
Symmetries provide the basis for well-established approaches to tackle the state explosion problem ...
Previous research in Artificial Intelligence has identified the possibility of simplifying planning ...
Symmetry-based state space pruning techniques have proved to greatly improve heuristic search based ...
Previous work in symmetry detection for planning has identified symmetries between domain objects an...
The exploitation of symmetry in combinatorial search has typically focused on using information abou...
Many planning problems exhibit a high degree of symmetry that cannot yet be exploited suc-cessfully ...
This thesis focuses on improving the process of automated planing through symmetry breaking. The aim...
State spaces in classical planning domains are usually quite large and can easily be extended to lar...
AbstractGeometrical symmetries are commonly exploited to improve the efficiency of search algorithms...
Since their introduction, symmetries have proven to be very powerful for the solution of different t...
Many planning problems contain collections of symmetric objects, actions and structures which render...