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variable and dynamic structure [132, 17, 131]. For modeling the
micro- and macro-level of a system, Multi-Level-DEVS (
ml
-
)
is proposed [133, 124] which connects the micro-level (i.e., a single
agent) with the macro-level. Therefore,
ml
-
Devs
(or some adaptation
of it taking variable structures into account) may be used for formally
describing an agent-based model. The major drawback of DEVS
(and the various variants of DEVS) is that the modeling is not very
intuitive and the resulting models become hard to understand quite
fast.
Devs
2.3.5 Agent-Object-Relationship Simulation
The Agent-Object-Relationship (AOR) modeling is an agent-oriented
approach for conceptual modeling of organizations and organizational
information systems, taking into account both static and dynamic
aspects [136]. In [139, 137] it is shown that this approach can also be
used for specifying simulation models.
The Agent-Object-Relationship Simulation (AORS) is developed
as an extension of traditional discrete event simulation. An AORS
simulation model consists of a model of the environment, a model for
each involved agent and a specification of the initial states for the
environment and for all agents. A time-stepped execution with fixed
time increments per cycle is assumed [137, 138]. Based on the ideas
of AOR modeling, the
Agent-Object-Relationship (AOR) Simulation
Language
is developed. It consists of an abstract model (described in
UML) and an according XML Schema defining the actual syntax.
The Agent-Object-Relationship Simulation (AORS) takes into ac-
count many important aspects of agent-based modeling and simulation.
Most notably the clear distinction between a simulation model and its
execution stands out. The simulation model can be expressed formally
(following the specified XML Schema) and independently of an actual
simulator executing it. The actual simulators in turn are based on an
abstract simulator. Thus, all parts are clearly separated from each
other and each part is based on a solid conceptual specification.
