Chapter 43
Game of Life
What I need is the dandelion in the spring. The bright yellow
that means rebirth instead of destruction. The promise that
life can go on, no matter how bad our losses. That it can be
good again.
(Suzanne Collins, Mockingjay)
43.1 Game of Life Model
Two of the most striking features of nature are the ability of these systems to evolve
and reproduce. For example, gradients in material concentrations and temperature
in the primordial soup enabled formation of simple structures that were not only
distinguishable from their environment but eventually also possessed the ability to
change that environment. The emergence of catalytic RNA in a heterogeneous
environment, in turn, not only led to change in the environment of these simple
structures but, with chance, to the change of these structures themselves [1]. Increasingly complex molecular structures evolved, reproduced, and continuously
transformed the environment in which they lived.
The evolution and reproduction of life forms was long interpreted as the result of
some “vital force.” It is only since the beginning of this century that we have gained
a better understanding of evolution and reproduction from a physical perspective
[2]. In 1966, John von Neumann created a simple model of a reproducing machine
[3] that sparked the development of numerous efforts to boil down rules for
replication to simple logical statements that take on the form of “mechanistic”
rules. Collectively, these models are known as cellular automata. In general, a
cellular automaton is any set of individuals with a finite number of characteristics
A save-disabled version of STELLA and the computer models of this book are available at
www.iseesystems.com/modelingdynamicbiologicalsystems.
B. Hannon and M. Ruth, Modeling Dynamic Biological Systems,
Modeling Dynamic Systems, DOI 10.1007/978-3-319-05615-9_43,
© Springer International Publishing Switzerland 2014
391
Game of Life
What I need is the dandelion in the spring. The bright yellow
that means rebirth instead of destruction. The promise that
life can go on, no matter how bad our losses. That it can be
good again.
(Suzanne Collins, Mockingjay)
43.1 Game of Life Model
Two of the most striking features of nature are the ability of these systems to evolve
and reproduce. For example, gradients in material concentrations and temperature
in the primordial soup enabled formation of simple structures that were not only
distinguishable from their environment but eventually also possessed the ability to
change that environment. The emergence of catalytic RNA in a heterogeneous
environment, in turn, not only led to change in the environment of these simple
structures but, with chance, to the change of these structures themselves [1]. Increasingly complex molecular structures evolved, reproduced, and continuously
transformed the environment in which they lived.
The evolution and reproduction of life forms was long interpreted as the result of
some “vital force.” It is only since the beginning of this century that we have gained
a better understanding of evolution and reproduction from a physical perspective
[2]. In 1966, John von Neumann created a simple model of a reproducing machine
[3] that sparked the development of numerous efforts to boil down rules for
replication to simple logical statements that take on the form of “mechanistic”
rules. Collectively, these models are known as cellular automata. In general, a
cellular automaton is any set of individuals with a finite number of characteristics
A save-disabled version of STELLA and the computer models of this book are available at
www.iseesystems.com/modelingdynamicbiologicalsystems.
B. Hannon and M. Ruth, Modeling Dynamic Biological Systems,
Modeling Dynamic Systems, DOI 10.1007/978-3-319-05615-9_43,
© Springer International Publishing Switzerland 2014
391