This purpose explains the interest of this game for biologists, since it explicitly aims to model a basic process in biology, the evolution of ecological communities (see Caballero et al., 2014). We show how this crucial function for practicing scientists can be found in the strategic use of versions that are usually dismissed by scientist as trivial and unserious.Ĭonway made connections with biology part of his purpose, bringing out “analogies with the rise, fall and alternations of a society of living organisms” ( Gardner, 1970). We see this second purpose, its “heuristic” or discovery function, as especially productive for biology. In this article we explore the merits for these purposes of a simulation game called “Life” by its creator, John Conway, “the Game of Life” by others. They provide judgment on the strengths of competing hypotheses, and generate unexpected or unsuspected possibilities for biologists to study and prove empirically. In recent times, computer simulations have played an increasingly important role in biology, in testing hypotheses and generating new ones. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We apply it to other biological processes, including symbiopoiesis. This game was designed to explore the evolution of ecological communities. Conway's Game of Life has been widely used for this purpose. 2Institute for Culture and Society, Western Sydney University, Parramatta, NSW, AustraliaĬellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories.1Centro de Ciencias de la Complejidad C3, Universidad Nacional Autónoma de México, Mexico City, Mexico.txt file is free by clicking on the export iconĬite as source (bibliography): Game of Life on dCode.Lorena Caballero 1 * Bob Hodge 2 Sergio Hernandez 1 The copy-paste of the page "Game of Life" or any of its results, is allowed (even for commercial purposes) as long as you cite dCode!Įxporting results as a. Except explicit open source licence (indicated Creative Commons / free), the "Game of Life" algorithm, the applet or snippet (converter, solver, encryption / decryption, encoding / decoding, ciphering / deciphering, breaker, translator), or the "Game of Life" functions (calculate, convert, solve, decrypt / encrypt, decipher / cipher, decode / encode, translate) written in any informatic language (Python, Java, PHP, C#, Javascript, Matlab, etc.) and all data download, script, or API access for "Game of Life" are not public, same for offline use on PC, mobile, tablet, iPhone or Android app! Ask a new question Source codeĭCode retains ownership of the "Game of Life" source code. The game of life has been created by John Horton Conway in 1970.
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