Learning Dynamics with Synchronous, Asynchronous and General Semantics

International audienceLearning from interpretation transition (LFIT) automatically constructs a model of the dynamics of a system from the observation of its state transitions. So far, the systems that LFIT handles are restricted to synchronous deterministic dynamics, i.e., all variables update their values at the same time and, for each state of the system, there is only one possible next state. However, other dynamics exist in the field of logical modeling, in particular the asynchronous semantics which is widely used to model biological systems. In this paper, we focus on a method that learns the dynamics of the system independently of its semantics. For this purpose, we propose a modeling of multi-valued systems as logic programs in which a rule represents what can occurs rather than what will occurs. This modeling allows us to represent non-determinism and to propose an extension of LFIT in the form of a semantics free algorithm to learn from discrete multi-valued transitions, regardless of their update schemes. We show through theoretical results that synchronous, asynchronous and general semantics are all captured by this method. Practical evaluation is performed on randomly generated systems and benchmarks from biological literature to study the scalabil-ity of this new algorithm regarding the three aforementioned semantics

Combining Knowledge and Metrics to Control Software Quality Factors

The LESD project (Linguistic Engineering for Software Development) aimed to develop computing tools for analysis and reasoning on functional or preliminary specifications of aerospace software written in English

Certifying Standard and Stratified Datalog Inference Engines in SSReflect

International audienceWe propose a SSReflect library for logic programming in the Datalog setting. As part of this work, we give a first mechanization of standard Datalog and of its extension with stratified negation. The library contains a formalization of the model theoretical and fix-point semantics of the languages, implemented through bottom-up and, respectively, through stratified evaluation procedures. We provide corresponding soundness, termination, completeness and model minimality proofs. To this end, we rely on the Coq proof assistant and SSReflect. In this context, we also construct a preliminary framework for dealing with stratified programs. We consider this to be a necessary first step towards the certification of security-aware data-centric applications

From failure to success : comparing a denotational and a declarative semantics for Horn clause logic

The main purpose of the paper is to relate different models for Horn Clause Logic: operational, denotational, declarative. We study their relationship by contrasting models based on interleaving, on the one hand, to models based on maximal parallelism, on the other. We make use of complete metric spaces as an important mathematical tool, both in defining and in comparing the various models