TY  - JOUR
A1  - Dimopoulos, Yannis
A1  - Gebser, Martin
A1  - Lühne, Patrick
A1  - Romero Davila, Javier
A1  - Schaub, Torsten
T1  - plasp 3
BT  - Towards Effective ASP Planning
JF  - Theory and practice of logic programming
N2  - We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.
KW  - knowledge representation and nonmonotonic reasoning
KW  - technical notes and rapid communications
KW  - answer set programming
KW  - automated planning
KW  - action and change
Y1  - 2019
U6  - https://doi.org/10.1017/S1471068418000583
SN  - 1471-0684
SN  - 1475-3081
VL  - 19
IS  - 3
SP  - 477
EP  - 504
PB  - Cambridge Univ. Press
CY  - New York
ER  - 
TY  - JOUR
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Kaufmann, Benjamin
A1  - Lühne, Patrick
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero Davila, Javier
A1  - Schaub, Torsten
A1  - Schellhorn, Sebastian
A1  - Wanko, Philipp
T1  - The Potsdam Answer Set Solving Collection 5.0
JF  - Künstliche Intelligenz
N2  - The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0528-x
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 181
EP  - 182
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - GEN
A1  - Alviano, Mario
A1  - Romero Davila, Javier
A1  - Schaub, Torsten
T1  - Preference Relations by Approximation
T2  - Sixteenth International Conference on Principles of Knowledge Representation and Reasoning
N2  - Declarative languages for knowledge representation and reasoning provide constructs to define preference relations over the set of possible interpretations, so that preferred models represent optimal solutions of the encoded problem. We introduce the notion of approximation for replacing preference relations with stronger preference relations, that is, relations comparing more pairs of interpretations. Our aim is to accelerate the computation of a non-empty subset of the optimal solutions by means of highly specialized algorithms. We implement our approach in Answer Set Programming (ASP), where problems involving quantitative and qualitative preference relations can be addressed by ASPRIN, implementing a generic optimization algorithm. Unlike this, chains of approximations allow us to reduce several preference relations to the preference relations associated with ASP’s native weak constraints and heuristic directives. In this way, ASPRIN can now take advantage of several highly optimized algorithms implemented by ASP solvers for computing optimal solutions
Y1  - 2018
SP  - 2
EP  - 11
PB  - AAAI Conference on Artificial Intelligence
CY  - Palo Alto
ER  -