Model checking ontology-driven reasoning agents using strategy and abstraction

We present a framework for the modelling, specification and verification of ontology-driven multi-agent rule-based systems (MASs). We assume that each agent executes in a separate process and that they communicate via message passing. The proposed approach makes use of abstract specifications to model the behaviour of some of the agents in the system, and exploits information about the reasoning strategy adopted by the agents. Abstract specifications are given as Linear Temporal Logic (LTL) formulas which describe the external behaviour of the agents, allowing their temporal behaviour to be compactly modelled. Both abstraction and strategy have been combined in an automated model checking encoding tool Tovrba for rule-based multi-agent systems which allows the system designer to specify information about agents' interaction, behaviour, and execution strategy at different levels of abstraction. The Tovrba tool generates an encoding of the system for the Maude LTL model checker, allowing properties of the system to be verified

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes amedium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes amedium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications

Ontology-based model-driven patterns for notification-oriented data-intensive enterprise information systems

International audienceIn the fourth industrial revolution, the current Enterprise Information Systems (EIS) are facing a set of new challenges raised by the applications of Cyber-Physical Systems (CPS) and Internet of Things (IoT). In this scenario, a data-intensive EIS involves networks of physical objects with sensing, data collection, transmission and actuation capabilities, and vast endpoints in the cloud, thereby offering large amounts of data. Such systems can be considered as a multidisciplinary complex system with strong interrelations between the involved components. In order to cope with the big heterogeneousness of those physical objects and their intrinsic information, the authors propose a notification-based approach derived from the so-called Notification Oriented Paradigm (NOP), a new rule and event driven approach for software and hardware specification and execution. However, the heterogeneity of those information and their interpretation relatively to an evolving context impose the definition of model-driven patterns based on some formal knowledge modelled by a set of skill-based ontologies. Thus, the paper focuses on the open issue related to the formalisation of such ontology-based patterns for their verification, ensuring the coherence of the whole set of data in each contextual engineering domain involved in the EIS

LogScope

LogScope is a software package for analyzing log files. The intended use is for offline post-processing of such logs, after the execution of the system under test. LogScope can, however, in principle, also be used to monitor systems online during their execution. Logs are checked against requirements formulated as monitors expressed in a rule-based specification language. This language has similarities to a state machine language, but is more expressive, for example, in its handling of data parameters. The specification language is user friendly, simple, and yet expressive enough for many practical scenarios. The LogScope software was initially developed to specifically assist in testing JPL s Mars Science Laboratory (MSL) flight software, but it is very generic in nature and can be applied to any application that produces some form of logging information (which almost any software does)

An Ontology-based approach to integrating life cycle analysis and computer aided design

Ponencia presentada en el XII Congreso Internacional de Ingeniería de Proyectos celebrado en Zaragoza en el año 2008One of the principal problems faced by engineering design today is the exchange of product information across different applications and environments. Ontological engineering systems, an evolution of KBE (Knowledge-Based Engineering) systems, seek to facilitate this integration while incorporating additional design information. An ontology, in the engineering domain, can be defined as an explicit specification of a shared conceptualization. This paper proposes the integration of an ontology with a Computer Aided Design (CAD) program, while also accessing a database of information on environmental impact. The proposed ontology is based on the AsD (Assembly Design) formalism, which describes spatial relationships and features of CAD models. The use of OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) ensures machine interpretability and exchange across different environments. Ultimately, the ontology will be used to represent a CAD model and related information (such as joining methods, materials, tolerances) in formal terms. Concurrently, a database of information on environmental impact of the materials, processes and transport involved will be accessed to evaluate the model on an environmental level. As a practical illustration, the evaluation of an underwater camera is used as an example

METAPLEX: AN INTEGRATED ENVIRONMENT FOR ORGANIZATION AND INFORMATION SYSTEMS DEVELOPMENT

This paper presents an integrated environment, called MetaPlex; for organization and information systems development. The kernel of MetaPlex is a knowledge base management system which captures the semantic primitives of a domain at the meta level and uses these primitives to describe target systems. Three levels of abstraction are used in MetaPlex for representing knowledge: the axiomatic, median, and instance levels. The MetaPlex Language Definition System is used to name the object types in the domain of interest and to define the attributes, relations, and descriptions which can be used by these object types. The structural knowledge of the domain in general is thus captured at the median level. Knowledge of the domain captured at the median level is used by the MetaPlex Specification System to define a target system at the instance level. A rule-based inference engine is embedded in the MetaPlex environment as an intelligent assistant to help end users. The expertise of a designer can be codified into a rule set which can assist users in classifying an object, in decomposing a high level system component, or in clustering the detailed components at the lower level. Both topdown and bottom-up approaches for systems development are thus supported. A layered approach has been proposed to manage the dynamics of such a metasystem environment. An enterprise model has been developed to demonstrate the usage of MetaPlex and the integration of organization and information systems modeling. Directions for future research are also discussed