26 research outputs found
Bounded LTL Model Checking with Stable Models
In this paper bounded model checking of asynchronous concurrent systems is
introduced as a promising application area for answer set programming. As the
model of asynchronous systems a generalisation of communicating automata,
1-safe Petri nets, are used. It is shown how a 1-safe Petri net and a
requirement on the behaviour of the net can be translated into a logic program
such that the bounded model checking problem for the net can be solved by
computing stable models of the corresponding program. The use of the stable
model semantics leads to compact encodings of bounded reachability and deadlock
detection tasks as well as the more general problem of bounded model checking
of linear temporal logic. Correctness proofs of the devised translations are
given, and some experimental results using the translation and the Smodels
system are presented.Comment: 32 pages, to appear in Theory and Practice of Logic Programmin
Encoding Higher Level Extensions of Petri Nets in Answer Set Programming
Answering realistic questions about biological systems and pathways similar
to the ones used by text books to test understanding of students about
biological systems is one of our long term research goals. Often these
questions require simulation based reasoning. To answer such questions, we need
formalisms to build pathway models, add extensions, simulate, and reason with
them. We chose Petri Nets and Answer Set Programming (ASP) as suitable
formalisms, since Petri Net models are similar to biological pathway diagrams;
and ASP provides easy extension and strong reasoning abilities. We found that
certain aspects of biological pathways, such as locations and substance types,
cannot be represented succinctly using regular Petri Nets. As a result, we need
higher level constructs like colored tokens. In this paper, we show how Petri
Nets with colored tokens can be encoded in ASP in an intuitive manner, how
additional Petri Net extensions can be added by making small code changes, and
how this work furthers our long term research goals. Our approach can be
adapted to other domains with similar modeling needs
A Polynomial Translation of Logic Programs with Nested Expressions into Disjunctive Logic Programs: Preliminary Report
Nested logic programs have recently been introduced in order to allow for
arbitrarily nested formulas in the heads and the bodies of logic program rules
under the answer sets semantics. Nested expressions can be formed using
conjunction, disjunction, as well as the negation as failure operator in an
unrestricted fashion. This provides a very flexible and compact framework for
knowledge representation and reasoning. Previous results show that nested logic
programs can be transformed into standard (unnested) disjunctive logic programs
in an elementary way, applying the negation as failure operator to body
literals only. This is of great practical relevance since it allows us to
evaluate nested logic programs by means of off-the-shelf disjunctive logic
programming systems, like DLV. However, it turns out that this straightforward
transformation results in an exponential blow-up in the worst-case, despite the
fact that complexity results indicate that there is a polynomial translation
among both formalisms. In this paper, we take up this challenge and provide a
polynomial translation of logic programs with nested expressions into
disjunctive logic programs. Moreover, we show that this translation is modular
and (strongly) faithful. We have implemented both the straightforward as well
as our advanced transformation; the resulting compiler serves as a front-end to
DLV and is publicly available on the Web.Comment: 10 pages; published in Proceedings of the 9th International Workshop
on Non-Monotonic Reasonin
Reasoning about Actions with Temporal Answer Sets
In this paper we combine Answer Set Programming (ASP) with Dynamic Linear
Time Temporal Logic (DLTL) to define a temporal logic programming language for
reasoning about complex actions and infinite computations. DLTL extends
propositional temporal logic of linear time with regular programs of
propositional dynamic logic, which are used for indexing temporal modalities.
The action language allows general DLTL formulas to be included in domain
descriptions to constrain the space of possible extensions. We introduce a
notion of Temporal Answer Set for domain descriptions, based on the usual
notion of Answer Set. Also, we provide a translation of domain descriptions
into standard ASP and we use Bounded Model Checking techniques for the
verification of DLTL constraints.Comment: To appear in Theory and Practice of Logic Programmin
Logic Programming for Finding Models in the Logics of Knowledge and its Applications: A Case Study
The logics of knowledge are modal logics that have been shown to be effective
in representing and reasoning about knowledge in multi-agent domains.
Relatively few computational frameworks for dealing with computation of models
and useful transformations in logics of knowledge (e.g., to support multi-agent
planning with knowledge actions and degrees of visibility) have been proposed.
This paper explores the use of logic programming (LP) to encode interesting
forms of logics of knowledge and compute Kripke models. The LP modeling is
expanded with useful operators on Kripke structures, to support multi-agent
planning in the presence of both world-altering and knowledge actions. This
results in the first ever implementation of a planner for this type of complex
multi-agent domains.Comment: 16 pages, 1 figure, International Conference on Logic Programming
201
Experiments with SAT-based Answer Set Programming
Answer Set Programming (ASP) emerged in the late 1990s as a new logic programming paradigm which has been successfully applied in various application domains. Propositional satisfiability (SAT) is one of the most studied problems in Computer Science. ASP and SAT are closely related: Recent works have studied their relation, and efficient SAT-based ASP solvers (like assat and Cmodels) exist. In this paper we report about (i) the extension of the basic procedures in Cmodels in order to incorporate the most popular SAT reasoning strategies, and (ii) an extensive comparative analysis involving also other state-of-the-art answer set solvers. The experimental analysis points out, besides the fact that Cmodels is highly competitive, that the reasoning strategies that work best on “small but hard” problems are ineffective on “big but easy” problems and vice-versa
Symmetry Breaking for Answer Set Programming
In the context of answer set programming, this work investigates symmetry
detection and symmetry breaking to eliminate symmetric parts of the search
space and, thereby, simplify the solution process. We contribute a reduction of
symmetry detection to a graph automorphism problem which allows to extract
symmetries of a logic program from the symmetries of the constructed coloured
graph. We also propose an encoding of symmetry-breaking constraints in terms of
permutation cycles and use only generators in this process which implicitly
represent symmetries and always with exponential compression. These ideas are
formulated as preprocessing and implemented in a completely automated flow that
first detects symmetries from a given answer set program, adds
symmetry-breaking constraints, and can be applied to any existing answer set
solver. We demonstrate computational impact on benchmarks versus direct
application of the solver.
Furthermore, we explore symmetry breaking for answer set programming in two
domains: first, constraint answer set programming as a novel approach to
represent and solve constraint satisfaction problems, and second, distributed
nonmonotonic multi-context systems. In particular, we formulate a
translation-based approach to constraint answer set solving which allows for
the application of our symmetry detection and symmetry breaking methods. To
compare their performance with a-priori symmetry breaking techniques, we also
contribute a decomposition of the global value precedence constraint that
enforces domain consistency on the original constraint via the unit-propagation
of an answer set solver. We evaluate both options in an empirical analysis. In
the context of distributed nonmonotonic multi-context system, we develop an
algorithm for distributed symmetry detection and also carry over
symmetry-breaking constraints for distributed answer set programming.Comment: Diploma thesis. Vienna University of Technology, August 201