Federico Banti

The Refined Extension Principle for Semantics of Dynamic Logic Programming

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. Such principle 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 generalisations of the stable model semantics, comply 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.

From logic programs updates to action description updates

An important branch of investigation in the field of agents has been the definition of high level languages for representing effects of actions, the programs written in such languages being usually called action programs. Logic programming is an important area in the field of knowledge representation and some languages for specifying updates of Logic Programs had been defined. Starting from the update language Evolp, in this work we propose a new paradigm for reasoning about actions called Evolp action programs. We provide translations of some of the most known action description languages into Evolp action programs, and underline some peculiar features of this newly defined paradigm. One such feature is that Evolp action programs can easily express changes in the rules of the domains, including rules describing changes.

The well supported semantics for multidimensional dynamic logic programs

Multidimensional dynamic logic programs are a paradigm which allows to express (partially) hierarchically ordered evolving knowledge bases through (partially) ordered multi sets of logic programs and allowing to solve contradictions among rules in different programs by allowing rules in more important programs to reject rules in less important ones. This class of programs extends the class of dynamic logic program that provides meaning and semantics to sequences of logic programs. Recently a semantics named refined stable model semantics has fixed some counterintuitive behaviour of previously existing semantics for dynamic logic programs. However, it is not possible to directly extend the definitions and concepts of the refined semantics to the multidimensional case and hence more sophisticated principles and techniques are in order. In this paper we face the problem of defining a proper semantics for multidimensional dynamic logic programs by extending the idea of well supported model to this class of programs and by showing that this concept alone is enough for univocally characterizing a proper semantics. We then show how the newly defined semantics coincides with the refined one when applied to sequences of programs.

Well Founded Semantics for Logic Program Updates

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.

Semantics for Dynamic Logic Programming: A Principle-Based Approach !

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.

Operational semantics for DyLPs

Theoretical research has spent some years facing the problem of how to represent and provide semantics to updates of logic programs. This problem is relevant for addressing highly dynamic domains with logic programming techniques. Two of the most recent results are the definition of the refined stable and the well founded semantics for dynamic logic programs that extend stable model and well founded semantic to the dynamic case. We present here alternative, although equivalent, operational characterizations of these semantics by program transformations into normal logic programs. The transformations provide new insights on the computational complexity of these semantics, a way for better understanding the meaning of the update programs, and also a methodology for the implementation of these semantics. In this sense, the equivalence theorems in this paper constitute soundness an completeness results for the implementations of these semantics.

Evolving reactive logic programs

In this paper we briefly describe the research activity that we have been carrying out during the last years on dynamic logic programs. After reviewing our contributions to strengthening the semantic foundations of dynamic logic programs, we describe a simple formalism to reason about actions —based on dynamic logic programs— and its event-condition-action extension that supports the specification and the execution of reactive programs.