Modeling Artificial Life: A Cellular Automata Approach - Computational Intelligence Techniques for Comparative Genomics - page 71

Keywords Evolution Natural selection Arti cial life Modeling life Arti cial

ecosystem Cellular automata Game of life Langton ' s ant Hodgepodge

1 Introduction

Computers today are used in all aspects of modern life. One of the major areas
where computers are widely used is coding. Many philosophical and theoretical
questions can be answered via modeling by the means of coding. The roots of
evolutionary design spring from the interaction between computer science, design
and evolutionary biology [ 1 ]. The broad areas of art, design, and architecture are
widely being used to build various applications today. A few of the applications
include transforming images, constructing architectural forms, constructing 3D
images and sculptures, applying various compositions, and visualization. The
process involves designing and applying rules based on real-time observations.
The rules governing the phenomenon are used to generate a network which models
the real-time scenario via a machine. Rules or the instructions are framed such that
they are straight forward and unambiguous. Simple local rules can often be used to
create unexpected and complex patterns. The central feature of framing the rules is
to explore in nite number of variations existing within a complex system [ 1 ]. Fast

iterations are explored via rules, and thereby, performance of the object is modeled.
The object behavior is merged with the complex interactions of the environment
while tracing and applying the applicable rules. Some behaviors which cannot be
predicted in advance due to persisting variations existing within the rules are
modeled with the variations, and the results are interpreted to further understand the
behavior of the environment. Repetitive tasks are built using looping constructs of
programming, to form digital patterns, [ 2 ] where the interaction between two or
more entities in an environment determine the future patterns or object states.
Digital patterns explore emergence which involves formation of higher-order
properties via interaction of lower-level elements.
An idea is conceptualized and turned into code using rule-based art and algo-
rithmic thinking [ 2 ], where a method or a procedure is described in an ambiguous
manner. Initially, a tangible physical process is taken which is abstractly translated
into a form which is suitable to express a process as an algorithm. The transition can
be generated in real time by means of a machine [ 3 ]. The algorithm is further
implemented as code using simple rules which are repeated over multiple objects
often generating complex phenomena. While expressing the algorithm, the degree
of simpli cation, proper judgment of important events, and simple patterns take

care of randomness and variation which are expressed when an unpredictable event
occurs. Decanting of a neurological pattern within a phenomenon being measured
and organism mutations creating new strands of organisms are a few other random