EUCLID RTP 6.1
Objectives
Recommendations
Conclusions
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EUCLID (EUropean Co-operation for the
Long term In Defence) is a
collaborative military research programme initiated by the Western European Armaments
Group. It is divided into a number of CEPAs (Common European Priority Areas), of
which CEPA 6 addresses Advanced Information Processing and Communications. CEPA 6 is
further divided into a number of Research and Technology Projects (RTPs).
The objective of EUCLID RTP 6.1 is to accelerate the application of
Artificial Intelligence (AI) and advanced software engineering and Human-Computer
Interaction (HCI) techniques to Command, Control, Communications and Intelligence (C3I) systems.
The secondary objectives are:
to develop intelligent tools for automated report analysis and
time-critical decision support, planning and tasking (DSPT) in the army and naval domains
to test the architecture and tools using simulations representing a
naval landing force scenario and an army peace enforcement scenario
to define and implement a workstation architecture able to
accommodate existing and emerging methods and tools, and to forge new standards
to encourage European collaboration in C3I
research and development.
RTP 6.1 is a highly collaborative project. Led by Logica UK Limited, it is undertaken by the GRACE
Consortium (Grouping for Research into Advanced C3I for Europe) comprising 17
companies from 7 nations: Denmark, France, Italy, Norway, the Netherlands, Spain and the
UK. The clients for the work are seven Ministries of Defence (MoDs) represented by a
Management Group (MG), chaired by the UKs Defence Evaluation and Research Agency
(DERA), Malvern.
EUCLID RTP 6.1 has produced an integrated demonstrator featuring two
key innovations:
an agent-based architecture to integrate diverse AI based
applications, and
an integrated suite of command decision support tools applying AI
technologies.
The integration architecture comprises:
Both CABLE and FIONA embrace the CORBA standard enabling
software to be distributed at run-time across a mixed network of Sun Solaris and PC
Windows-NT workstations. CABLE, FIONA and the FUN (Functional Unit)
Methodology for specifying and designing multi-agent systems are particularly well suited
to distributed, intelligent decision support and modelling and simulation applications,
whether military or not. At the time of writing 10 new projects, most in the UK, have
exploited this architecture, with a total value of 2 MECU (£1.4M).
The project has developed tools using a wide range of AI techniques, to
support different aspects of army and naval situation assessment and planning:
report analysis and construction of a wide area picture
a common object model used across all tools to represent situation
and encyclopaedic data
analysis of enemy behaviours and generation of alerts
map display, terrain analysis and calculation of intervisibility
areas
manoeuvre planning
planning, scheduling and synchronisation
what-if simulation
scheduling and time constraint calculations
resource allocation and engagement co-ordination.
The tools were designed to support the human command team, by
automating only those aspects of a task that are better suited to the machine. The
benefits typically found from using AI techniques, compared with manual planning, are:
automatic alerting to significant events or changes in the situation
quicker planning, while considering more alternative plans
better compliance with complex constraints on time, space, terrain
and resources.
The project was carried out between Autumn 1993 and Autumn 1998. The
project has developed about 800,000 lines of new C++ code, 14 different C3I
tools and a powerful integration architecture. These have been developed using 125 man
years of effort at a cost overall of around 16 MECU to the participating MoDs and 5 MECU
to the participating companies. It is therefore important that all participating MoDs and
companies achieve a high level of exploitation of the software and techniques developed. A
programme re-using just 10% of the RTP 6.1 software - 1 or 2 tools and 80,000 lines of
code - will potentially save 10 man years effort.
It is expected that the main route for exploitation will be into
applied research programmes and technology demonstrators within national military research
programmes. These need to adapt the RTP 6.1 work to particular national military
applications, systems and architectures.
There are two distinct elements of the work that can be exploited - the
architecture (CABLE/FIONA) and the tools. Re-using individual
tools is relatively easy, since in most cases the novel techniques used are embodied in
C++ code that is independent of the RTP 6.1 architecture. Exploiting the multi-agent
architecture is a bigger commitment, which may be difficult in existing operational
systems, but which provides major advantages in terms of ease of integration and of
distribution over a heterogeneous architecture supporting multiple users. These are
pre-requisites for next generation systems.
The RTP 6.1 demonstrator will be available for demonstrations at
Logicas Cambridge, UK office to June 2000. Partial demonstrators are available in
other GRACE companies.
Full sets of paper documentation are available in Logica, DERA
Malvern and each participating MoD. Partial documentation sets are available in other
GRACE companies.
A CD of project documents and software is available to participating
companies and MoDs from Logica.
An FTP site
(with password protection) is available to participating companies and MoDs for
downloading software and documents.
RTP 6.1 has demonstrated what can be achieved today by integrating COTS
software, and applying and adapting AI techniques to C3I. Two general
recommendations emerge:
There is no one AI technique, or family of techniques, to solve all
problems: for each problem tackled, a suitable AI technique must be selected, even though
this means the final system uses a wide range of different techniques working together
Architectures and standards need to enable software to be distributed
over a heterogeneous network of computers, to support multiple, co-operating users and to
simplify integration of legacy, COTS and new software from different sources.
A service-based multi-agent architecture incorporating a range of AI
techniques can meet these requirements.
See also the consortiums Objectives, Recommendations, and Conclusions.
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Produced by: Peter Martin / Russell Gordon /
Mike Pockney
Updated: 01 April 1999
Copyright Logica 1999 |
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