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X-Machines for Agent-Based Modeling: FLAME Perspectives
1.4 Importance of Emergence
Goldstein [74] argues that “emergence refers to rising of novel and coherent structured patterns and properties during the process of self-organization
of complex systems”. But Anderson [8] points out that due to scale and complexity, it is not necessary that the built model would always turn out to be
same as its individual real parts. This notion leads to the fact that emergence
itself cannot be defined as a perfect pattern with multiple result possibilities.
“The ability to reduce everything to simple fundamental laws does
not imply the ability to start from those laws and reconstruct the universe. The constructionist hypothesis breaks down when confronted with
the twin difficulties of scale and complexity. At each level of complexity
entirely new properties appear. Psychology is not applied biology, nor
is biology applied chemistry. We can see that the whole becomes not
merely more, but very different from sum of its parts.” [8]
Modeling a system is the process of creating a replica of the system. This
could be done by considering only a few aspects of what is needed to be observed from that system, or what modelers desire to test. For instance, testing
small gears working together in a clock could either be tested with individual
elements modeled as gears, or whole collection of gears connected to the needle, taken as one individual. Modeling depends on modeler requirements to
how they want to represent the system.
The model would also be simulated a number of times to understand its
average behavior. Randomness in complex systems can sometimes lead to
unpredictable patterns, which makes testing a concrete part of modeling.
1.5 Dynamic Systems
Complex systems can adapt to changing environmental conditions. Their
ability to cope with changes and their survival makes systems extremely robust
and favorable for inspirations in engineering applications. Traditionally, numerical equations with differentiation are used to represent dynamic systems
as functions with respect to time. Examples of such equations are Newton’s
law of motion for particles and forces, represented as expressions of velocity, acceleration during movement and direction of travel for particles. The
Navier-Stokes equations are used to describe motion of fluid substances, used
X-Machines for Agent-Based Modeling: FLAME Perspectives
1.4 Importance of Emergence
Goldstein [74] argues that “emergence refers to rising of novel and coherent structured patterns and properties during the process of self-organization
of complex systems”. But Anderson [8] points out that due to scale and complexity, it is not necessary that the built model would always turn out to be
same as its individual real parts. This notion leads to the fact that emergence
itself cannot be defined as a perfect pattern with multiple result possibilities.
“The ability to reduce everything to simple fundamental laws does
not imply the ability to start from those laws and reconstruct the universe. The constructionist hypothesis breaks down when confronted with
the twin difficulties of scale and complexity. At each level of complexity
entirely new properties appear. Psychology is not applied biology, nor
is biology applied chemistry. We can see that the whole becomes not
merely more, but very different from sum of its parts.” [8]
Modeling a system is the process of creating a replica of the system. This
could be done by considering only a few aspects of what is needed to be observed from that system, or what modelers desire to test. For instance, testing
small gears working together in a clock could either be tested with individual
elements modeled as gears, or whole collection of gears connected to the needle, taken as one individual. Modeling depends on modeler requirements to
how they want to represent the system.
The model would also be simulated a number of times to understand its
average behavior. Randomness in complex systems can sometimes lead to
unpredictable patterns, which makes testing a concrete part of modeling.
1.5 Dynamic Systems
Complex systems can adapt to changing environmental conditions. Their
ability to cope with changes and their survival makes systems extremely robust
and favorable for inspirations in engineering applications. Traditionally, numerical equations with differentiation are used to represent dynamic systems
as functions with respect to time. Examples of such equations are Newton’s
law of motion for particles and forces, represented as expressions of velocity, acceleration during movement and direction of travel for particles. The
Navier-Stokes equations are used to describe motion of fluid substances, used