4,051 research outputs found
Recycling Computed Answers in Rewrite Systems for Abduction
In rule-based systems, goal-oriented computations correspond naturally to the
possible ways that an observation may be explained. In some applications, we
need to compute explanations for a series of observations with the same domain.
The question whether previously computed answers can be recycled arises. A yes
answer could result in substantial savings of repeated computations. For
systems based on classic logic, the answer is YES. For nonmonotonic systems
however, one tends to believe that the answer should be NO, since recycling is
a form of adding information. In this paper, we show that computed answers can
always be recycled, in a nontrivial way, for the class of rewrite procedures
that we proposed earlier for logic programs with negation. We present some
experimental results on an encoding of the logistics domain.Comment: 20 pages. Full version of our IJCAI-03 pape
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
Computing abduction by using TMS with top-down expectation
AbstractWe present a method to compute abduction in logic programming. We translate an abductive framework into a normal logic program with integrity constraints and show the correspondence between generalized stable models and stable models for the translation of the abductive framework. Abductive explanations for an observation can be found from the stable models for the translated program by adding a special kind of integrity constraint for the observation. Then, we show a bottom-up procedure to compute stable models for a normal logic program with integrity constraints. The proposed procedure excludes the unnecessary construction of stable models on early stages of the procedure by checking integrity constraints during the construction and by deriving some facts from integrity constraints. Although a bottom-up procedure has the disadvantage of constructing stable models not related to an observation for computing abductive explanations in general, our procedure avoids the disadvantage by expecting which rule should be used for satisfaction of integrity constraints and starting bottom-up computation based on the expectation. This expectation is not only a technique to scope rule selection but also an indispensable part of our stable model construction because the expectation is done for dynamically generated constraints as well as the constraint for the observation
Multi-agent planning using an abductive : event calculus
Temporal reasoning within distributed Artificial Intelligence Systems is faced with the problem of concurrent streams of action. Well known, logic-based systems using the SITUATION CALCULUS solve the frame problem in a purely linear manner. Recent research, however, has revealed that the EVENT CALCULUS under the abduction principle is capable of nonlinear planning. In this report, we present a planning service module which incorporates this approach into a constraint logic framework and even allows a notion of strong nonlinearity. The work includes the axiomatisation of appropriate versions of the EVENT CALCULUS, the development of a suitably sound and complete proof procedure that supports abduction and the implementation of both of these layers on the constraint platform OZ. We demonstrate prototypically how this module, EVE, can be integrated into an existing multi-agent architecture and evaluate the behaviour of such agents within an application domain, the loading dock scenario
Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations
Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em InformáticaAfter a very brief introduction to the general subject of Knowledge Representation and Reasoning with Logic Programs we analyse the syntactic structure of a logic program and how it can influence the semantics. We outline the important properties of a 2-valued semantics for Normal Logic Programs, proceed to define the new Minimal Hypotheses semantics with those properties and explore how it can be used to benefit some knowledge representation and reasoning mechanisms.
The main original contributions of this work, whose connections will be detailed in
the sequel, are:
• The Layering for generic graphs which we then apply to NLPs yielding the Rule
Layering and Atom Layering — a generalization of the stratification notion;
• The Full shifting transformation of Disjunctive Logic Programs into (highly nonstratified)NLPs;
• The Layer Support — a generalization of the classical notion of support;
• The Brave Relevance and Brave Cautious Monotony properties of a 2-valued semantics;
• The notions of Relevant Partial Knowledge Answer to a Query and Locally Consistent
Relevant Partial Knowledge Answer to a Query;
• The Layer-Decomposable Semantics family — the family of semantics that reflect
the above mentioned Layerings;
• The Approved Models argumentation approach to semantics;
• The Minimal Hypotheses 2-valued semantics for NLP — a member of the Layer-Decomposable Semantics family rooted on a minimization of positive hypotheses assumption approach;
• The definition and implementation of the Answer Completion mechanism in XSB
Prolog — an essential component to ensure XSB’s WAM full compliance with the
Well-Founded Semantics;
• The definition of the Inspection Points mechanism for Abductive Logic Programs;• An implementation of the Inspection Points workings within the Abdual system [21]
We recommend reading the chapters in this thesis in the sequence they appear. However,
if the reader is not interested in all the subjects, or is more keen on some topics
rather than others, we provide alternative reading paths as shown below.
1-2-3-4-5-6-7-8-9-12 Definition of the Layer-Decomposable Semantics family and the Minimal Hypotheses semantics (1 and 2 are optional)
3-6-7-8-10-11-12 All main contributions – assumes the reader
is familiarized with logic programming topics
3-4-5-10-11-12 Focus on abductive reasoning and applications.FCT-MCTES (Fundação para a Ciência e Tecnologia do Ministério da Ciência,Tecnologia e Ensino Superior)- (no. SFRH/BD/28761/2006
Machine ethics via logic programming
Machine ethics is an interdisciplinary field of inquiry that emerges from the need of
imbuing autonomous agents with the capacity of moral decision-making. While some
approaches provide implementations in Logic Programming (LP) systems, they have not
exploited LP-based reasoning features that appear essential for moral reasoning.
This PhD thesis aims at investigating further the appropriateness of LP, notably a
combination of LP-based reasoning features, including techniques available in LP systems,
to machine ethics. Moral facets, as studied in moral philosophy and psychology, that
are amenable to computational modeling are identified, and mapped to appropriate LP
concepts for representing and reasoning about them.
The main contributions of the thesis are twofold.
First, novel approaches are proposed for employing tabling in contextual abduction
and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets.
Second, a variety of LP-based reasoning features are applied to model the identified
moral facets, through moral examples taken off-the-shelf from the morality literature.
These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.Fundação para a Ciência e a Tecnologia (FCT)-grant SFRH/BD/72795/2010 ; CENTRIA
and DI/FCT/UNL for the supplementary fundin
A Parameterised Hierarchy of Argumentation Semantics for Extended Logic Programming and its Application to the Well-founded Semantics
Argumentation has proved a useful tool in defining formal semantics for
assumption-based reasoning by viewing a proof as a process in which proponents
and opponents attack each others arguments by undercuts (attack to an
argument's premise) and rebuts (attack to an argument's conclusion). In this
paper, we formulate a variety of notions of attack for extended logic programs
from combinations of undercuts and rebuts and define a general hierarchy of
argumentation semantics parameterised by the notions of attack chosen by
proponent and opponent. We prove the equivalence and subset relationships
between the semantics and examine some essential properties concerning
consistency and the coherence principle, which relates default negation and
explicit negation. Most significantly, we place existing semantics put forward
in the literature in our hierarchy and identify a particular argumentation
semantics for which we prove equivalence to the paraconsistent well-founded
semantics with explicit negation, WFSX. Finally, we present a general proof
theory, based on dialogue trees, and show that it is sound and complete with
respect to the argumentation semantics.Comment: To appear in Theory and Practice of Logic Programmin
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