In this paper, we analyze an Artificial Micro-World (AMW), obtained by evolving 2D k-totalistic Cellular Automata by Genetic Algorithms. Using the metaphor of an Artificial Laboratory, in which we examine artificial species as zoologists do, we evolve the Micro-World from initial random conditions and find artificial self-replicating species, with different behaviors. By isolating these species from their environment, we simulate their behavior in a different settings, to see if their behavior is the same or different in various simulation conditions. Then, as well as in examples of genetic engineering, we put together the structures of two artificial organisms, belonging to two different species and analyze the result of their behaviors. Finally, we analyze the global dynamics of the colony formation within this Micro-World. As a result, we found that there are different occurring dynamics. Some dynamics are typical of self-reproducers, gliders and glider-guns. But other growing systems give rise to nested dynamics, that allows processes of increasing complexity.

ARTIFICIAL MICRO-WORLDS. PART II: CELLULAR AUTOMATA GROWTH DYNAMICS

BILOTTA, Eleonora;PANTANO, Pietro Salvatore
2011

Abstract

In this paper, we analyze an Artificial Micro-World (AMW), obtained by evolving 2D k-totalistic Cellular Automata by Genetic Algorithms. Using the metaphor of an Artificial Laboratory, in which we examine artificial species as zoologists do, we evolve the Micro-World from initial random conditions and find artificial self-replicating species, with different behaviors. By isolating these species from their environment, we simulate their behavior in a different settings, to see if their behavior is the same or different in various simulation conditions. Then, as well as in examples of genetic engineering, we put together the structures of two artificial organisms, belonging to two different species and analyze the result of their behaviors. Finally, we analyze the global dynamics of the colony formation within this Micro-World. As a result, we found that there are different occurring dynamics. Some dynamics are typical of self-reproducers, gliders and glider-guns. But other growing systems give rise to nested dynamics, that allows processes of increasing complexity.
Cellular automata; artificial micro-world; self-replicator
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/139733
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