3,527 research outputs found
Applications of Intuitionistic Logic in Answer Set Programming
We present some applications of intermediate logics in the field of Answer
Set Programming (ASP). A brief, but comprehensive introduction to the answer
set semantics, intuitionistic and other intermediate logics is given. Some
equivalence notions and their applications are discussed. Some results on
intermediate logics are shown, and applied later to prove properties of answer
sets. A characterization of answer sets for logic programs with nested
expressions is provided in terms of intuitionistic provability, generalizing a
recent result given by Pearce.
It is known that the answer set semantics for logic programs with nested
expressions may select non-minimal models. Minimal models can be very important
in some applications, therefore we studied them; in particular we obtain a
characterization, in terms of intuitionistic logic, of answer sets which are
also minimal models. We show that the logic G3 characterizes the notion of
strong equivalence between programs under the semantic induced by these models.
Finally we discuss possible applications and consequences of our results. They
clearly state interesting links between ASP and intermediate logics, which
might bring research in these two areas together.Comment: 30 pages, Under consideration for publication in Theory and Practice
of Logic Programmin
Embedding Non-Ground Logic Programs into Autoepistemic Logic for Knowledge Base Combination
In the context of the Semantic Web, several approaches to the combination of
ontologies, given in terms of theories of classical first-order logic and rule
bases, have been proposed. They either cast rules into classical logic or limit
the interaction between rules and ontologies. Autoepistemic logic (AEL) is an
attractive formalism which allows to overcome these limitations, by serving as
a uniform host language to embed ontologies and nonmonotonic logic programs
into it. For the latter, so far only the propositional setting has been
considered. In this paper, we present three embeddings of normal and three
embeddings of disjunctive non-ground logic programs under the stable model
semantics into first-order AEL. While the embeddings all correspond with
respect to objective ground atoms, differences arise when considering
non-atomic formulas and combinations with first-order theories. We compare the
embeddings with respect to stable expansions and autoepistemic consequences,
considering the embeddings by themselves, as well as combinations with
classical theories. Our results reveal differences and correspondences of the
embeddings and provide useful guidance in the choice of a particular embedding
for knowledge combination.Comment: 52 pages, submitte
Bisimulation and expressivity for conditional belief, degrees of belief, and safe belief
Plausibility models are Kripke models that agents use to reason about
knowledge and belief, both of themselves and of each other. Such models are
used to interpret the notions of conditional belief, degrees of belief, and
safe belief. The logic of conditional belief contains that modality and also
the knowledge modality, and similarly for the logic of degrees of belief and
the logic of safe belief. With respect to these logics, plausibility models may
contain too much information. A proper notion of bisimulation is required that
characterises them. We define that notion of bisimulation and prove the
required characterisations: on the class of image-finite and preimage-finite
models (with respect to the plausibility relation), two pointed Kripke models
are modally equivalent in either of the three logics, if and only if they are
bisimilar. As a result, the information content of such a model can be
similarly expressed in the logic of conditional belief, or the logic of degrees
of belief, or that of safe belief. This, we found a surprising result. Still,
that does not mean that the logics are equally expressive: the logics of
conditional and degrees of belief are incomparable, the logics of degrees of
belief and safe belief are incomparable, while the logic of safe belief is more
expressive than the logic of conditional belief. In view of the result on
bisimulation characterisation, this is an equally surprising result. We hope
our insights may contribute to the growing community of formal epistemology and
on the relation between qualitative and quantitative modelling
Logic Programming with Default, Weak and Strict Negations
This paper treats logic programming with three kinds of negation: default,
weak and strict negations. A 3-valued logic model theory is discussed for logic
programs with three kinds of negation. The procedure is constructed for
negations so that a soundness of the procedure is guaranteed in terms of
3-valued logic model theory.Comment: 14 pages, to appear in Theory and Practice of Logic Programming
(TPLP
Characterizing downwards closed, strongly first order, relativizable dependencies
In Team Semantics, a dependency notion is strongly first order if every
sentence of the logic obtained by adding the corresponding atoms to First Order
Logic is equivalent to some first order sentence. In this work it is shown that
all nontrivial dependency atoms that are strongly first order, downwards
closed, and relativizable (in the sense that the relativizations of the
corresponding atoms with respect to some unary predicate are expressible in
terms of them) are definable in terms of constancy atoms.
Additionally, it is shown that any strongly first order dependency is safe
for any family of downwards closed dependencies, in the sense that every
sentence of the logic obtained by adding to First Order Logic both the strongly
first order dependency and the downwards closed dependencies is equivalent to
some sentence of the logic obtained by adding only the downwards closed
dependencies
Modular Logic Programming: Full Compositionality and Conflict Handling for Practical Reasoning
With the recent development of a new ubiquitous nature of data and the profusity
of available knowledge, there is nowadays the need to reason from multiple sources
of often incomplete and uncertain knowledge. Our goal was to provide a way to
combine declarative knowledge bases – represented as logic programming modules
under the answer set semantics – as well as the individual results one already inferred
from them, without having to recalculate the results for their composition and without
having to explicitly know the original logic programming encodings that produced
such results. This posed us many challenges such as how to deal with fundamental
problems of modular frameworks for logic programming, namely how to define a
general compositional semantics that allows us to compose unrestricted modules.
Building upon existing logic programming approaches, we devised a framework
capable of composing generic logic programming modules while preserving the
crucial property of compositionality, which informally means that the combination of
models of individual modules are the models of the union of modules. We are also
still able to reason in the presence of knowledge containing incoherencies, which is
informally characterised by a logic program that does not have an answer set due
to cyclic dependencies of an atom from its default negation. In this thesis we also
discuss how the same approach can be extended to deal with probabilistic knowledge
in a modular and compositional way.
We depart from the Modular Logic Programming approach in Oikarinen &
Janhunen (2008); Janhunen et al. (2009) which achieved a restricted form of compositionality
of answer set programming modules. We aim at generalising this
framework of modular logic programming and start by lifting restrictive conditions
that were originally imposed, and use alternative ways of combining these (so called
by us) Generalised Modular Logic Programs. We then deal with conflicts arising
in generalised modular logic programming and provide modular justifications and
debugging for the generalised modular logic programming setting, where justification
models answer the question: Why is a given interpretation indeed an Answer Set?
and Debugging models answer the question: Why is a given interpretation not an
Answer Set?
In summary, our research deals with the problematic of formally devising a
generic modular logic programming framework, providing: operators for combining
arbitrary modular logic programs together with a compositional semantics; We
characterise conflicts that occur when composing access control policies, which are
generalisable to our context of generalised modular logic programming, and ways of
dealing with them syntactically: provided a unification for justification and debugging
of logic programs; and semantically: provide a new semantics capable of dealing
with incoherences. We also provide an extension of modular logic programming
to a probabilistic setting. These goals are already covered with published work. A prototypical tool implementing the unification of justifications and debugging is
available for download from http://cptkirk.sourceforge.net
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Fallibilism and Multiple Paths to Knowledge (Extended Version)
This chapter argues that epistemologists should replace a “standard alternatives” picture of knowledge, assumed by many fallibilist theories of knowledge, with a new “multipath” picture of knowledge. The chapter first identifies a problem for the standard picture: fallibilists working with this picture cannot maintain even the most uncontroversial epistemic closure principles without making extreme assumptions about the ability of humans to know empirical truths without empirical investigation. The chapter then shows how the multipath picture, motivated by independent arguments, saves fallibilism from this problem. The multipath picture is based on taking seriously the idea that there can be multiple paths to knowing some propositions about the world. An overlooked consequence of fallibilism is that these multiple paths to knowledge may involve ruling out different sets of alternatives, which should be represented in a fallibilist picture of knowledge. The chapter concludes by considering inductive knowledge and strong epistemic closure from this multipath perspective
A System of Interaction and Structure
This paper introduces a logical system, called BV, which extends
multiplicative linear logic by a non-commutative self-dual logical operator.
This extension is particularly challenging for the sequent calculus, and so far
it is not achieved therein. It becomes very natural in a new formalism, called
the calculus of structures, which is the main contribution of this work.
Structures are formulae submitted to certain equational laws typical of
sequents. The calculus of structures is obtained by generalising the sequent
calculus in such a way that a new top-down symmetry of derivations is observed,
and it employs inference rules that rewrite inside structures at any depth.
These properties, in addition to allow the design of BV, yield a modular proof
of cut elimination.Comment: This is the authoritative version of the article, with readable
pictures, in colour, also available at
. (The published version contains
errors introduced by the editorial processing.) Web site for Deep Inference
and the Calculus of Structures at <http://alessio.guglielmi.name/res/cos
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