97,591 research outputs found
Boosting Answer Set Optimization with Weighted Comparator Networks
Answer set programming (ASP) is a paradigm for modeling knowledge intensive
domains and solving challenging reasoning problems. In ASP solving, a typical
strategy is to preprocess problem instances by rewriting complex rules into
simpler ones. Normalization is a rewriting process that removes extended rule
types altogether in favor of normal rules. Recently, such techniques led to
optimization rewriting in ASP, where the goal is to boost answer set
optimization by refactoring the optimization criteria of interest. In this
paper, we present a novel, general, and effective technique for optimization
rewriting based on comparator networks, which are specific kinds of circuits
for reordering the elements of vectors. The idea is to connect an ASP encoding
of a comparator network to the literals being optimized and to redistribute the
weights of these literals over the structure of the network. The encoding
captures information about the weight of an answer set in auxiliary atoms in a
structured way that is proven to yield exponential improvements during
branch-and-bound optimization on an infinite family of example programs. The
used comparator network can be tuned freely, e.g., to find the best size for a
given benchmark class. Experiments show accelerated optimization performance on
several benchmark problems.Comment: 36 page
Scalable Design Space Exploration via Answer Set Programming
The design of embedded systems is becoming continuously more complex such that the application of efficient high level design methods are crucial for competitive results regarding design time and performance. Recently, advances in Boolean constraint solvers for Answer Set Programming (ASP) allow for easy integration of background theories and more control over the solving process. The goal of this research is to leverage those advances for system level design space exploration while using specialized techniques from electronic design automation that drive new application-originated ideas for multi-objective combinatorial optimization
Logic Programming approaches for routing fault-free and maximally-parallel Wavelength Routed Optical Networks on Chip (Application paper)
One promising trend in digital system integration consists of boosting
on-chip communication performance by means of silicon photonics, thus
materializing the so-called Optical Networks-on-Chip (ONoCs). Among them,
wavelength routing can be used to route a signal to destination by univocally
associating a routing path to the wavelength of the optical carrier. Such
wavelengths should be chosen so to minimize interferences among optical
channels and to avoid routing faults. As a result, physical parameter selection
of such networks requires the solution of complex constrained optimization
problems. In previous work, published in the proceedings of the International
Conference on Computer-Aided Design, we proposed and solved the problem of
computing the maximum parallelism obtainable in the communication between any
two endpoints while avoiding misrouting of optical signals. The underlying
technology, only quickly mentioned in that paper, is Answer Set Programming
(ASP). In this work, we detail the ASP approach we used to solve such problem.
Another important design issue is to select the wavelengths of optical
carriers such that they are spread across the available spectrum, in order to
reduce the likelihood that, due to imperfections in the manufacturing process,
unintended routing faults arise. We show how to address such problem in
Constraint Logic Programming on Finite Domains (CLP(FD)).
This paper is under consideration for possible publication on Theory and
Practice of Logic Programming.Comment: Paper presented at the 33nd International Conference on Logic
Programming (ICLP 2017), Melbourne, Australia, August 28 to September 1,
2017. 16 pages, LaTeX, 5 figure
The Design of the Fifth Answer Set Programming Competition
Answer Set Programming (ASP) is a well-established paradigm of declarative
programming that has been developed in the field of logic programming and
nonmonotonic reasoning. Advances in ASP solving technology are customarily
assessed in competition events, as it happens for other closely-related
problem-solving technologies like SAT/SMT, QBF, Planning and Scheduling. ASP
Competitions are (usually) biennial events; however, the Fifth ASP Competition
departs from tradition, in order to join the FLoC Olympic Games at the Vienna
Summer of Logic 2014, which is expected to be the largest event in the history
of logic. This edition of the ASP Competition series is jointly organized by
the University of Calabria (Italy), the Aalto University (Finland), and the
University of Genova (Italy), and is affiliated with the 30th International
Conference on Logic Programming (ICLP 2014). It features a completely
re-designed setup, with novelties involving the design of tracks, the scoring
schema, and the adherence to a fixed modeling language in order to push the
adoption of the ASP-Core-2 standard. Benchmark domains are taken from past
editions, and best system packages submitted in 2013 are compared with new
versions and solvers.
To appear in Theory and Practice of Logic Programming (TPLP).Comment: 10 page
The DLV System for Knowledge Representation and Reasoning
This paper presents the DLV system, which is widely considered the
state-of-the-art implementation of disjunctive logic programming, and addresses
several aspects. As for problem solving, we provide a formal definition of its
kernel language, function-free disjunctive logic programs (also known as
disjunctive datalog), extended by weak constraints, which are a powerful tool
to express optimization problems. We then illustrate the usage of DLV as a tool
for knowledge representation and reasoning, describing a new declarative
programming methodology which allows one to encode complex problems (up to
-complete problems) in a declarative fashion. On the foundational
side, we provide a detailed analysis of the computational complexity of the
language of DLV, and by deriving new complexity results we chart a complete
picture of the complexity of this language and important fragments thereof.
Furthermore, we illustrate the general architecture of the DLV system which
has been influenced by these results. As for applications, we overview
application front-ends which have been developed on top of DLV to solve
specific knowledge representation tasks, and we briefly describe the main
international projects investigating the potential of the system for industrial
exploitation. Finally, we report about thorough experimentation and
benchmarking, which has been carried out to assess the efficiency of the
system. The experimental results confirm the solidity of DLV and highlight its
potential for emerging application areas like knowledge management and
information integration.Comment: 56 pages, 9 figures, 6 table
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