Efficient Representation of Pattern Databases Using Acyclic Random Hypergraphs. Sadeqi, M. & Hamilton, H. In
Paper abstract bibtex 2 downloads A popular way for creating domain-independent heuristic functions is by using abstraction, an abstract (coarse) version of the state space. Abstraction-based heuristic is usually implemented using a pattern database, a lookup table of (abstract state, heuristic value) pairs. Efficient representation and compression of pattern databases has been the topic of substantial amount of ongoing research. In this paper, we present a novel domain-independent algorithm for this purpose using acyclic $r$-partite random hypergraphs. The theoretical and experimental results show that our proposed algorithm provides a consistent representation that works well across many planning problem domains and provides a very good trade-off for space usage and lookup time. This makes it suitable as a standard efficient representation for pattern databases and a benchmark method for other pattern database representation/compression methods.
@inproceedings {icaps16-126,
track = {Main Track},
title = {Efficient Representation of Pattern Databases Using Acyclic Random Hypergraphs},
url = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13093},
author = {Mehdi Sadeqi and Howard Hamilton},
abstract = {A popular way for creating domain-independent heuristic functions is by using abstraction, an abstract (coarse) version of the state space. Abstraction-based heuristic is usually implemented using a pattern database, a lookup table of (abstract state, heuristic value) pairs. Efficient representation and compression of pattern databases has been the topic of substantial amount of ongoing research. In this paper, we present a novel domain-independent algorithm for this purpose using acyclic $r$-partite random hypergraphs. The theoretical and experimental results show that our proposed algorithm provides a consistent representation that works well across many planning problem domains and provides a very good trade-off for space usage and lookup time. This makes it suitable as a standard efficient representation for pattern databases and a benchmark method for other pattern database representation/compression methods.},
keywords = {Search techniques}
}