14
X-Machines for Agent-Based Modeling: FLAME Perspectives
A
B
C
I n p u t s f r o m
t h e e n v i r o n m e n t
O u t p u t
F e e d b a c k f r o m o u t p u t
a f f e c t s i n p u t s
FIGURE 1.7: A system working in the environment. The system is composed
of three elements working together to make the system work efficiently. Output
produces a feedback, that produces change in the system as time progresses.
Cellular Automata
Cellular automata models have stemmed from basics of computational
theory, mathematics and biology. Developed by Ulam and von Neumann [198],
they were able to prove the notion of one robot producing another robot or
also known as ‘the principle of self-replicating systems’. A famous example is
the ‘Game of Life’ by John Conway which uses four simple rules of generations.
Here, every element is treated as a cell that transitions based on strict rules
predefined by life generations [159].
Being used as a more powerful computational model [203], principles of
cellular automata allow individual cells to react and change their states based
on their surrounding neighboring cells. If visualized as a plane of cells, there
can be a pattern that is observed moving across from one point to other, by
subsequent reaction of cells. For example, vibration of molecules in a solid,
when provided with heat, acts as a wave propagating from one point to other.
Agent-Based Models
The word agent has multiple definitions by different modelers. With respect to agent-based models, the following definition is used in this book:
“An agent is a computer system that is situated in some environment,
and that is capable of autonomous action in this environment in order
to meet its design goals” Wooldridge and Jennings [205]
It does not specify that every gear in a clock be modeled as one agent or
the whole unit to be treated as one agent to reach model goals. This allows
modelers to define their own agents and their behaviors per model.
X-Machines for Agent-Based Modeling: FLAME Perspectives
A
B
C
I n p u t s f r o m
t h e e n v i r o n m e n t
O u t p u t
F e e d b a c k f r o m o u t p u t
a f f e c t s i n p u t s
FIGURE 1.7: A system working in the environment. The system is composed
of three elements working together to make the system work efficiently. Output
produces a feedback, that produces change in the system as time progresses.
Cellular Automata
Cellular automata models have stemmed from basics of computational
theory, mathematics and biology. Developed by Ulam and von Neumann [198],
they were able to prove the notion of one robot producing another robot or
also known as ‘the principle of self-replicating systems’. A famous example is
the ‘Game of Life’ by John Conway which uses four simple rules of generations.
Here, every element is treated as a cell that transitions based on strict rules
predefined by life generations [159].
Being used as a more powerful computational model [203], principles of
cellular automata allow individual cells to react and change their states based
on their surrounding neighboring cells. If visualized as a plane of cells, there
can be a pattern that is observed moving across from one point to other, by
subsequent reaction of cells. For example, vibration of molecules in a solid,
when provided with heat, acts as a wave propagating from one point to other.
Agent-Based Models
The word agent has multiple definitions by different modelers. With respect to agent-based models, the following definition is used in this book:
“An agent is a computer system that is situated in some environment,
and that is capable of autonomous action in this environment in order
to meet its design goals” Wooldridge and Jennings [205]
It does not specify that every gear in a clock be modeled as one agent or
the whole unit to be treated as one agent to reach model goals. This allows
modelers to define their own agents and their behaviors per model.