142,064 research outputs found
Handling Defeasibilities in Action Domains
Representing defeasibility is an important issue in common sense reasoning.
In reasoning about action and change, this issue becomes more difficult because
domain and action related defeasible information may conflict with general
inertia rules. Furthermore, different types of defeasible information may also
interfere with each other during the reasoning. In this paper, we develop a
prioritized logic programming approach to handle defeasibilities in reasoning
about action. In particular, we propose three action languages {\cal AT}^{0},
{\cal AT}^{1} and {\cal AT}^{2} which handle three types of defeasibilities in
action domains named defeasible constraints, defeasible observations and
actions with defeasible and abnormal effects respectively. Each language with a
higher superscript can be viewed as an extension of the language with a lower
superscript. These action languages inherit the simple syntax of {\cal A}
language but their semantics is developed in terms of transition systems where
transition functions are defined based on prioritized logic programs. By
illustrating various examples, we show that our approach eventually provides a
powerful mechanism to handle various defeasibilities in temporal prediction and
postdiction. We also investigate semantic properties of these three action
languages and characterize classes of action domains that present more
desirable solutions in reasoning about action within the underlying action
languages.Comment: 49 pages, 1 figure, to be appeared in journal Theory and Practice
Logic Programmin
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
Abduction in Well-Founded Semantics and Generalized Stable Models
Abductive logic programming offers a formalism to declaratively express and
solve problems in areas such as diagnosis, planning, belief revision and
hypothetical reasoning. Tabled logic programming offers a computational
mechanism that provides a level of declarativity superior to that of Prolog,
and which has supported successful applications in fields such as parsing,
program analysis, and model checking. In this paper we show how to use tabled
logic programming to evaluate queries to abductive frameworks with integrity
constraints when these frameworks contain both default and explicit negation.
The result is the ability to compute abduction over well-founded semantics with
explicit negation and answer sets. Our approach consists of a transformation
and an evaluation method. The transformation adjoins to each objective literal
in a program, an objective literal along with rules that ensure
that will be true if and only if is false. We call the resulting
program a {\em dual} program. The evaluation method, \wfsmeth, then operates on
the dual program. \wfsmeth{} is sound and complete for evaluating queries to
abductive frameworks whose entailment method is based on either the
well-founded semantics with explicit negation, or on answer sets. Further,
\wfsmeth{} is asymptotically as efficient as any known method for either class
of problems. In addition, when abduction is not desired, \wfsmeth{} operating
on a dual program provides a novel tabling method for evaluating queries to
ground extended programs whose complexity and termination properties are
similar to those of the best tabling methods for the well-founded semantics. A
publicly available meta-interpreter has been developed for \wfsmeth{} using the
XSB system.Comment: 48 pages; To appear in Theory and Practice in Logic Programmin
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