Model Composability: Experiences with Military Simulation Systems
Dr. Marko A. Hofmann
Institute for Technology of Intelligent Systems (ITIS) and
Institute for Applied Systems Science and Operations Research (IASFOR)
University of the Federal Armed Forces Munich
Heisenbergweg 39
Germany - 85577 Neubiberg
Tel: ++49 89 6004 3242
Fax: ++49 89 6004 3036
marko@informatik.unibw-muenchen.de
Abstract : Model designers necessarily abstract and simplify reality according to their own perception,
preferences, purposes and conceptions, thus models - even of the same real system - regularly differ in several
aspects. Lessons learned with military simulation system indicate that technical and syntactic aspects of model
composition, which have been in the focus of interest for almost a decade, are not sufficient to guarantee
successful interaction. The crucial task is to ensure that syntactical structures are attributed with the same
meanings in all involved models, that the same actions are triggered by identical orders and reports and last but
not least that the abstractions from reality to the models do not contradict themselves. From this point of view
composability becomes a much more challenging task than the mere coupling of software components.
1. INTRODUCTION
In order to successfully build whole executable
models (programs) with model components it
is necessary to ensure that the conceptual models
underlying the executable models are in line with
each other. But since model designers necessarily
abstract and simplify reality according to their own
perception, preferences, purposes and conceptions,
models regularly differ in several aspects.
Experiences with military simulation system have
shown that there are essential preconditions for
coupling such “model based” information systems
(see for example [1] and [2]). Our results indicate
that technical and syntactic preconditions, which
have been in the focus of interest for almost a
decade, are not sufficient to guarantee a successful
interaction. The crucial tasks are to ensure that
syntactical structures are attributed with the same
meanings in all involved models and that the same
actions are triggered by identical orders and reports.
These findings have been confirmed during a study
we performed for the German Armed Forces
addressing the standardization of command and
control components for different Army simulation
systems. As a consequence of the importance of
meanings and triggered actions we have chosen a
“linguistic” approach to understand the problems of
interoperability, which is based on the idea of
successful communication between models/model
users. In linguistics one generally presupposes the
existence of a technical communication channel
(which is so important in computer science) and
concentrates on the three semiotic aspects of
language which are syntax, semantics and
pragmatics. Linguistics provide a perfect
framework for investigations into the meaning of
interactions, since the whole point of setting up a
theory of semantics and pragmatics is to provide a
systematic account of the nature of meaning.
Communication is successful if and only if sender
and receiver have common knowledge on all
semiotic aspects. In addition, composability is
restricted to models whose abstractions from reality
or, more general, whose conceptual modelling ideas
are in line with each other. Thus, interoperability of
model components is much more than the coupling
of simple technical devices, which has been the
predominant but misleading idea in the field of
military simulations for almost a decade. Some of
the costly consequences of this misconception can
be found in [3]. This paper aims at a further
clarification of the challenges of coupling models.
Since the mere presentation of coupling
problems stemming from a limited amount of
models would be too anecdotic and idiosyncratic to
be convincing, the paper first introduces a general
framework (sections 2 – 4) in which the examples
presented in chapter 5 fit as illustrations of the basic
ideas.
2. MODEL BASED INFORMATION
PROCESSING SYSTEMS
From a general point of view information
processing systems can be distinguished into direct
and intermediate control information systems (see
Figure 1). Most of the (artificial) information
processing systems used today are embedded into
real systems in which they operate as control units.
Their task is to ensure that the state transition of the
real system stays within a given trajectory. Such
information processing systems exert direct control
.....