Objective
Objectives:
Model based Reasoning is the symbolic processing of an explicit representation of the internal workings of a system in order to predict, simulate and explain the resultant behaviour of the system from the structure, causality and behaviour of its components. Qualitative models aim to capture the fundamental aspects of a system or mechanism, while suppressing much of the detail. Methods such as abstraction and approximation are often used to build models based on symbolic rather than numeric quantity spaces.
This Network aims to provide a long-term framework for research integration and co-operation that will
- co-ordinate European research in MB & QR systems, and
- promote technology transfer into industry.
It is intended that the network should be open to all those who can contribute to technological progress in MB & QR systems.
Activities:
- Aid the transfer of MB & QR systems technology to industrial applications
- Co-ordinate European MB & QR systems research and initiate co-operative projects
- Increase understanding and awareness of the key topics in MB & QR systems
- Organise information about industrial applications of MB & QR systems
- Survey the field and identify opportunities and target applications
Activity areas:
Research Fields - Within the area of model and qualitative reasoning systems we are including most forms of model-based reasoning and qualitative simulation, including: Functional and causal modelling; qualitative modelling; modelling ontologies; abstraction, aggregation and approximation; integration of mixed models; qualitative spatial modelling, kinematics and dynamics.
Application domains - The technology has a wide range of applications in many domains, including: Process modelling and simulation; design, configuration and planning; vision and language processing; geographical information systems; diagnosis, explanation and monitoring; control, prediction and interpretation.
Industrial sectors - An important aspect of the network will be the identification of application opportunities, technological gaps and targets for research into MB and QR systems. At present we have industrial nodes from the following industrial sectors: Automotive and Aerospace, Information Technology, National Utilities, Health Care, Process Industries, Manufacturing Systems, Biotechnology.
Interdisciplinary skills:
The interdisciplinary nature of the Network is essential for the successful transfer of MB & QR systems into industry. Within the network we therefore have a correct mix of organisations and institutions to ensure successful transfer of the technology - this includes research institutions (such as UWA and LAAS), high technology SMEs (OOC'M Software GmbH and Intelligent Applications Ltd) and large systems providers (Siemens and Bosch) as well as end users (Jaguar and Daimler-Benz) who can work together, via the network, to achieve successful technology transfer. The network will bring together expertise in the form of techniques, demonstrators, documentation, experts, users and potential users, for mutual exploitation.
Logistical support:
All nodes must have a technical interest in MONET, i.e. be active in MB & QR systems by using or developing applications or developing theory. By ensuring that the network has active nodes in both theory and applications the aims of technology transfer, in both directions, will be facilitated. Good communications between nodes will be provided by MONET; these will include Email, the World Wide Web and Newsletters. The MONET information repository will contain software systems and models, profiles of researchers and catalogues of other data that will support the objectives. MONET will also support a programme of visits, exchanges, seminars, summer schools, workshops and conferences.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences knowledge engineering ontology
- natural sciences computer and information sciences software software applications system software
- natural sciences computer and information sciences internet world wide web
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Data not available
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
SY23 2AX Aberystwyth
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.