10
X-Machines for Agent-Based Modeling: FLAME Perspectives
a collection of various smaller systems intertwined, have to modeled as
open systems.
Systems are dynamically changing. The environment around the individuals is constantly changing, influencing their behavior.
Display emergent behavior. The emerging behavior can be studied at
macro levels. For instance, insect colonies achieve their goals quicker
by working collusively among individual ants.
Individuals are adaptive. Depending on the changing environment and
available system resources, individuals adapt their behavior to survive
in given conditions.
Individuals are selfish. All individuals work for their own benefit using
local information.
1.8 Modeling and Simulation
Modeling and Simulation (M&S) is a core research area under scientific
computing, where artificial systems are created as models and simulated in
a virtual environment. Executing them in a virtual environment allows to
safely assume changes, in order, to predict how the system would behave
when certain changes are introduced in real world situations.
However, it is important to note that a model is only an approximate representation of the system, showing only basic functionalities being explored.
It is often a very simple representation of the system, with clearly defined
assumptions embed into the model while it is constructed.
A model is a representation of an object, a system or an idea represented
in a form other than that of the entity itself [175]. Simulation allows the model
to be tested in a virtual world to check its reaction to certain conditions. The
model’s design would ensure how reliable it is for making predictions.
There are multiple forms in which models are created, such as physical,
where models are constructed as prototypes, or scale models, where they represent systems, and mathematical, where models are constructed as analytical
mathematical notations, linear and simulation-based representations. In all
cases, techniques chosen to construct models, depend on the objectives and
aims of the modelers. Model examples include, but are not limited to,
• Engineering applications: Test if certain temperatures will affect smooth
running of the engine. These include examples from designing and analyzing manufacturing systems or transport systems.
X-Machines for Agent-Based Modeling: FLAME Perspectives
a collection of various smaller systems intertwined, have to modeled as
open systems.
Systems are dynamically changing. The environment around the individuals is constantly changing, influencing their behavior.
Display emergent behavior. The emerging behavior can be studied at
macro levels. For instance, insect colonies achieve their goals quicker
by working collusively among individual ants.
Individuals are adaptive. Depending on the changing environment and
available system resources, individuals adapt their behavior to survive
in given conditions.
Individuals are selfish. All individuals work for their own benefit using
local information.
1.8 Modeling and Simulation
Modeling and Simulation (M&S) is a core research area under scientific
computing, where artificial systems are created as models and simulated in
a virtual environment. Executing them in a virtual environment allows to
safely assume changes, in order, to predict how the system would behave
when certain changes are introduced in real world situations.
However, it is important to note that a model is only an approximate representation of the system, showing only basic functionalities being explored.
It is often a very simple representation of the system, with clearly defined
assumptions embed into the model while it is constructed.
A model is a representation of an object, a system or an idea represented
in a form other than that of the entity itself [175]. Simulation allows the model
to be tested in a virtual world to check its reaction to certain conditions. The
model’s design would ensure how reliable it is for making predictions.
There are multiple forms in which models are created, such as physical,
where models are constructed as prototypes, or scale models, where they represent systems, and mathematical, where models are constructed as analytical
mathematical notations, linear and simulation-based representations. In all
cases, techniques chosen to construct models, depend on the objectives and
aims of the modelers. Model examples include, but are not limited to,
• Engineering applications: Test if certain temperatures will affect smooth
running of the engine. These include examples from designing and analyzing manufacturing systems or transport systems.