Paper Info
Title
Ricochet Robots: A Transverse ASP Benchmark.
Abstract
A distinguishing feature of Answer Set Programming is its versatility. In addition to satisfiability testing, it offers various forms of model enumeration, intersection or unioning, as well as optimization. Moreover, there is an increasing interest in incremental and reactive solving due to their applicability to dynamic domains. However, so far no comparative studies have been conducted, contrasting the respective modeling capacities and their computational impact. To assess the variety of different forms of ASP solving, we propose Alex Randolph's board game Ricochet Robots as a transverse benchmark problem that allows us to compare various approaches in a uniform setting. To begin with, we consider alternative ways of encoding ASP planning problems and discuss the underlying modeling techniques. In turn, we conduct an empirical analysis contrasting traditional solving, optimization, incremental, and reactive approaches. In addition, we study the impact of some boosting techniques in the realm of our case study.
Year
DOI
Venue
2013
10.1007/978-3-642-40564-8_35
Lecture Notes in Computer Science
Field
DocType
Volume
Ricochet,Computer science,Satisfiability,Algorithm,Theoretical computer science,Data integrity,Boosting (machine learning),Robot,Answer set programming,Encoding (memory)
Conference
8148
ISSN
Citations 
PageRank 
0302-9743
7
0.56
References 
Authors
13
7
Name
Order
Citations
PageRank
Martin Gebser1190990.30
Holger Jost270.56
Roland Kaminski364231.79
Philipp Obermeier4668.04
Orkunt Sabuncu5748.39
Torsten Schaub63150191.50
Marius Schneider72308.21