Updates of Logic Programs by Logic Programs

1999

Most of the work conducted so far in the field of logic programming has focused on representing static knowledge, i.e. knowledge that does not evolve with time. To overcome this limitation, in a recent paper, the authors introduced the concept of dynamic logic programming. There, they studied and defined the declarative and operational semantics of sequences of logic programs (or dynamic logic programs), P0 ⊕...⊕Pn. Each such program contains knowledge about some given state, where different states may, e.g., represent different time periods or different sets of priorities. The role of dynamic logic programming is to employ relationships existing between the possibly mutually contradictory sequence of programs to precisely determine, at any given state, the declarative and procedural semantics of their combination. But how, in concrete situations, is a sequence of logic programs built? For instance, in the domain of actions, what are the appropriate sequences of programs that represent the performed actions and their effects? Whereas dynamic logic programming provides a way for determining what should follow, given the sequence of programs, it does not provide a good practical language for the specification of updates or changes in the knowledge represented by successive logic programs. In this paper we define a language designed for specifying changes to logic programs (LUPS - “Language for dynamic updates”). Given an initial knowledge base (in the form of a logic program) LUPS provides a way for sequentially updating it. The declarative meaning of a sequence of sets of update actions in LUPS is defined using the semantics of the dynamic logic program generated by those actions. We also provide a translation of the sequence of update statements sets into a single generalized logic program written in a meta-language, so that the stable models of the resulting program correspond to the previously defined declarative semantics. This meta-language is used in the actual implementation, although his is not the subject of this paper. Finally we briefly mention related work (lack of space prevents us from presenting more detailed comparisons).

Lecture Notes in Computer Science, 2004

Over the last years various semantics have been proposed for dealing with updates of logic programs by (other) logic programs. Most of these semantics extend the stable models semantics of normal, extended (with explicit negation) or generalized (with default negation in rule heads) logic programs. In this paper we propose a well founded semantics for logic programs updates. We motivate our proposal with both practical and theoretical argumentations. Various theoretical results presented here show how our proposal is related to the stable model approach and how it extends the well founded semantics of normal and generalized logic programs.

2000

Over the last years various semantics have been proposed for dealing with updates in the setting of logic programs. The availability of dierent semantics naturally raises the question of which are the most adequate to model updates. A systematic approach to face this question is to identify general principles against which such semantics should be tested. In this paper we

Theoretical Computer Science, 1997

We provide a simple formulation of a framework where some extensions of logic programming with non-monotonic reasoning are treated uniformly, namely, two kinds of negation and abduction. The resulting semantics is purely model-theoretic, and gives meaning to any noncontradictory abductive logic program. Moreover, it embeds and generalizes some existing semantics which deal with negation and abduction. The framework is equipped with a correct top-down proof procedure.

2001

Recently, several approaches for updating knowledge bases represented as logic programs have been proposed. In this paper, we present a generic framework for declarative specifications of update policies, which is built upon such approaches. It extends the LUPS language for update specifications and incorporates the notion of events into the framework. An update policy allows an agent to flexibly react upon new information, arriving as an event, and perform suitable changes of its knowledge base. The framework compiles update policies to logic programs by means of generic translations, and can be instantiated in terms of different concrete update approaches. It thus provides a flexible tool for designing adaptive reasoning agents.

Lecture Notes in Computer Science, 1997

Lecture Notes in Computer Science, 2003

Over recent years, various semantics have been proposed for dealing with updates in the setting of logic programs. The availability of different semantics naturally raises the question of which are most adequate to model updates. A systematic approach to face this question is to identify general principles against which such semantics could be evaluated. In this paper we motivate and introduce a new such principle -the refined extension principle -which is complied with by the stable model semantics for (single) logic programs. It turns out that none of the existing semantics for logic program updates, even though based on stable models, complies with this principle. For this reason, we define a refinement of the dynamic stable model semantics for Dynamic Logic Programs that complies with the principle.