In this paper we describe novel representations for precomputed heuristics based on Level-Ordered Edge Sequence (LOES) encodings. We introduce compressed LOES, an extension to LOES that enables more aggressive compression of the state-set representation. We evaluate the novel repre- sentations against the respective perfect-hash and binary decision diagram (BDD) representations of pattern databases in a variety of STRIPS domains
We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extra...
Pattern mining based on data compression has been successfully applied in many data mining tasks. Fo...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. D...
A popular way to create domain-independent heuristic functions is by using abstraction, where an ab...
We introduce the level-ordered edge sequence (LOES), a suc- cinct encoding for state-sets based on p...
The heuristics used for planning and search often take the form of pattern databases generated from ...
One common pattern database compression technique is to merge adjacent database entries and store th...
We present a new technique to compress pattern databases to provide consistent heuristics without lo...
A pattern database (PDB) is a heuristic function implemented as a lookup table that stores the lengt...
Abstract. A pattern database (PDB) is a heuristic function implemented as a lookup table. It stores ...
We present an algorithm for compressing pattern databases (PDBs) and a method for fast random access...
Pattern mining is one of the best-known concepts in Data Mining. A big problem in pattern mining is ...
The manipulation of large sequence data is one of the most important problems in string processing. ...
Most modern lossless data compression techniques used today, are based in dictionaries. If some stri...
We introduce a general framework which is suitable to capture an essence of compressed pattern match...
We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extra...
Pattern mining based on data compression has been successfully applied in many data mining tasks. Fo...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. D...
A popular way to create domain-independent heuristic functions is by using abstraction, where an ab...
We introduce the level-ordered edge sequence (LOES), a suc- cinct encoding for state-sets based on p...
The heuristics used for planning and search often take the form of pattern databases generated from ...
One common pattern database compression technique is to merge adjacent database entries and store th...
We present a new technique to compress pattern databases to provide consistent heuristics without lo...
A pattern database (PDB) is a heuristic function implemented as a lookup table that stores the lengt...
Abstract. A pattern database (PDB) is a heuristic function implemented as a lookup table. It stores ...
We present an algorithm for compressing pattern databases (PDBs) and a method for fast random access...
Pattern mining is one of the best-known concepts in Data Mining. A big problem in pattern mining is ...
The manipulation of large sequence data is one of the most important problems in string processing. ...
Most modern lossless data compression techniques used today, are based in dictionaries. If some stri...
We introduce a general framework which is suitable to capture an essence of compressed pattern match...
We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extra...
Pattern mining based on data compression has been successfully applied in many data mining tasks. Fo...
Abstraction heuristics are the state of the art in optimal classical planning as heuristic search. D...
DOI
Add to ORKG