Answer Set Programming with Composed Predicate Names

2020 ◽  
Author(s):  
Mario Alviano
Keyword(s):  
Answer Set Programming ◽  
Proof Of Concept ◽  
Input Program ◽  
Declarative Semantics ◽  
Answer Set ◽  
Lack Of Knowledge

Mainstream systems for Answer Set Programming implement intelligent grounding to eliminate object variables from the input program, often obtaining a propositional program of reasonable size. However, non-stratified negation may inhibit the simplification of some rule bodies due to the lack of knowledge on the truth of recursive atoms. Frustration is greatest when the program is clearly locally stratified, such as in case of numerical arguments in rule heads obtained by increasing some body arguments; common examples are minimal distances in graphs and time arguments in planning scenarios. This paper suggests to move some arguments in predicate names, so that the declarative semantics of Answer Set Programming is preserved, but non-stratified negation is possibly avoided thanks to symbolic rule instantiation. A proof of concept is given in terms of Jinja templates for arguments with a clear range.

scholarly journals The Impact of Treewidth on Grounding and Solving of Answer Set Programs

2020 ◽  
Vol 67 ◽  
pp. 35-80
Author(s):  
Bernhard Bliem ◽  
Michael Morak ◽  
Marius Moldovan ◽  
Stefan Woltran
Keyword(s):  
Parameterized Complexity ◽  
Answer Set Programming ◽  
Data Complexity ◽  
Bounded Treewidth ◽  
Input Program ◽  
The Impact ◽  
Disjunctive Programs ◽  
Np Hardness ◽  
Input Instance ◽  
Answer Set

In this paper, we aim to study how the performance of modern answer set programming (ASP) solvers is influenced by the treewidth of the input program and to investigate the consequences of this relationship. We first perform an experimental evaluation that shows that the solving performance is heavily influenced by treewidth, given ground input programs that are otherwise uniform, both in size and construction. This observation leads to an important question for ASP, namely, how to design encodings such that the treewidth of the resulting ground program remains small. To this end, we study two classes of disjunctive programs, namely guarded and connection-guarded programs. In order to investigate these classes, we formalize the grounding process using MSO transductions. Our main results show that both classes guarantee that the treewidth of the program after grounding only depends on the treewidth (and the maximum degree, in case of connection-guarded programs) of the input instance. In terms of parameterized complexity, our findings yield corresponding FPT results for answer-set existence for bounded treewidth (and also degree, for connection-guarded programs) of the input instance. We further show that bounding treewidth alone leads to NP-hardness in the data complexity for connection-guarded programs, which indicates that the two classes are fundamentally different. Finally, we show that for both classes, the data complexity remains as hard as in the general case of ASP.

scholarly journals Parallel instantiation of ASP programs: techniques and experiments

2012 ◽  
Vol 13 (2) ◽  
pp. 253-278 ◽  
Author(s):  
SIMONA PERRI ◽  
FRANCESCO RICCA ◽  
MARCO SIRIANNI
Keyword(s):  
Input Data ◽  
Search Algorithm ◽  
Answer Set Programming ◽  
Second Step ◽  
Backtracking Search ◽  
Processing Power ◽  
Input Program ◽  
Real World Applications ◽  
Symmetric Multiprocessing ◽  
Answer Set

AbstractAnswer-Set Programming (ASP) is a powerful logic-based programming language, which is enjoying increasing interest within the scientific community and (very recently) in industry. The evaluation of Answer-Set Programs is traditionally carried out in two steps. At the first step, an input program undergoes the so-called instantiation (or grounding) process, which produces a program ′ semantically equivalent to , but not containing any variable; in turn, ′ is evaluated by using a backtracking search algorithm in the second step. It is well-known that instantiation is important for the efficiency of the whole evaluation, might become a bottleneck in common situations, is crucial in several real-world applications, and is particularly relevant when huge input data have to be dealt with. At the time of this writing, the available instantiator modules are not able to exploit satisfactorily the latest hardware, featuring multi-core/multi-processor Symmetric MultiProcessing technologies. This paper presents some parallel instantiation techniques, including load-balancing and granularity control heuristics, which allow for the effective exploitation of the processing power offered by modern Symmetric MultiProcessing machines. This is confirmed by an extensive experimental analysis reported herein.

scholarly journals Shared aggregate sets in answer set programming

2018 ◽  
Vol 18 (3-4) ◽  
pp. 301-318 ◽  
Author(s):  
MARIO ALVIANO ◽  
CARMINE DODARO ◽  
MARCO MARATEA
Keyword(s):  
Empirical Evidence ◽  
Data Structures ◽  
Answer Set Programming ◽  
Input Program ◽  
Memory Footprint ◽  
Potential Impact ◽  
Truth Value ◽  
Answer Set

AbstractAggregates are among the most frequently used linguistic extensions of answer set programming. The result of an aggregation may introduce new constants during the instantiation of the input program, a feature known as value invention. When the aggregation involves literals whose truth value is undefined at instantiation time, modern grounders introduce several instances of the aggregate, one for each possible interpretation of the undefined literals. This paper introduces new data structures and techniques to handle such cases, and more in general aggregations on the same aggregate set identified in the ground program in input. The proposed solution reduces the memory footprint of the solver without sacrificing efficiency. On the contrary, the performance of the solver may improve thanks to the addition of some simple entailed clauses which are not easily discovered otherwise, and since redundant computation is avoided during propagation. Empirical evidence of the potential impact of the proposed solution is given.

scholarly journals Lazy-Grounding for Answer Set Programs with External Source Access

2017 ◽  
Author(s):  
Thomas Eiter ◽  
Tobias Kaminski ◽  
Antonius Weinzierl
Keyword(s):  
Efficient Solution ◽  
Answer Set Programming ◽  
External Source ◽  
Logic Programs ◽  
Real World Application ◽  
Input Program ◽  
Evaluation Algorithm ◽  
External Sources ◽  
New Perspective ◽  
Answer Set

HEX-programs enrich the well-known Answer Set Programming (ASP) paradigm. In HEX, problems are solved using nonmonotonic logic programs with bidirectional access to external sources. ASP evaluation is traditionally based on grounding the input program first, but recent advances in lazy-grounding make the latter also interesting for HEX, as the grounding bottleneck of ASP may be avoided. We explore this issue and present a new evaluation algorithm for HEX-programs based on lazy-grounding solving for ASP. Nonmonotonic dependencies and value invention (i.e., import of new constants) from external sources make an efficient solution nontrivial. However, illustrative benchmarks show a clear advantage of the new algorithm for grounding-intense programs, which is a new perspective to make HEX more suitable for real-world application needs.

scholarly journals The Impact of Treewidth on ASP Grounding and Solving

2017 ◽  
Author(s):  
Bernhard Bliem ◽  
Marius Moldovan ◽  
Michael Morak ◽  
Stefan Woltran
Keyword(s):  
Experimental Evaluation ◽  
Answer Set Programming ◽  
Input Program ◽  
The Impact ◽  
Input Instance ◽  
Answer Set

In this paper, we aim to study how the performance of modern answer set programming (ASP) solvers is influenced by the treewidth of the input program and to investigate the consequences of this relationship. We first perform an experimental evaluation that shows that the solving performance is heavily influenced by the treewidth, given ground input programs that are otherwise uniform, both in size and construction. This observation leads to an important question for ASP, namely, how to design encodings such that the treewidth of the resulting ground program remains small. To this end, we define the class of connection-guarded programs, which guarantees that the treewidth of the program after grounding only depends on the treewidth (and the degree) of the input instance. In order to obtain this result, we formalize the grounding process using MSO transductions.

scholarly journals Open answer set programming with guarded programs

2008 ◽  
Vol 9 (4) ◽  
pp. 1-53 ◽  
Author(s):  
Stijn Heymans ◽  
Davy Van Nieuwenborgh ◽  
Dirk Vermeir
Keyword(s):  
Answer Set Programming ◽  
Answer Set

scholarly journals Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming

2013 ◽  
Vol 29 (18) ◽  
pp. 2320-2326 ◽  
Author(s):  
Carito Guziolowski ◽  
Santiago Videla ◽  
Federica Eduati ◽  
Sven Thiele ◽  
Thomas Cokelaer ◽  
...  
Keyword(s):  
Answer Set Programming ◽  
Signaling Network ◽  
Logic Models ◽  
Answer Set

CoreALMlib: An library translated from the Component Library

2016 ◽  
Vol 16 (5-6) ◽  
pp. 800-816 ◽  
Author(s):  
DANIELA INCLEZAN
Keyword(s):  
Natural Language ◽  
Answer Set Programming ◽  
Natural Language Understanding ◽  
Inference Engine ◽  
Lexical Resources ◽  
Language Understanding ◽  
Commonsense Knowledge ◽  
Component Library ◽  
Action Language ◽  
Answer Set

AbstractThis paper presents CoreALMlib, an $\mathscr{ALM}$ library of commonsense knowledge about dynamic domains. The library was obtained by translating part of the Component Library (CLib) into the modular action language $\mathscr{ALM}$. CLib consists of general reusable and composable commonsense concepts, selected based on a thorough study of ontological and lexical resources. Our translation targets CLibstates (i.e., fluents) and actions. The resulting $\mathscr{ALM}$ library contains the descriptions of 123 action classes grouped into 43 reusable modules that are organized into a hierarchy. It is made available online and of interest to researchers in the action language, answer-set programming, and natural language understanding communities. We believe that our translation has two main advantages over its CLib counterpart: (i) it specifies axioms about actions in a more elaboration tolerant and readable way, and (ii) it can be seamlessly integrated with ASP reasoning algorithms (e.g., for planning and postdiction). In contrast, axioms are described in CLib using STRIPS-like operators, and CLib's inference engine cannot handle planning nor postdiction.

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