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Morphozoic, Cellular Automata with Nested Neighborhoods as a Metamorphic Representation of Morphogenesis
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Author(s): Thomas Portegys (Dialectek, USA), Gabriel Pascualy (University of Michigan, USA), Richard Gordon (Gulf Specimen Marine Laboratory and Wayne State University, USA), Stephen P. McGrew (New Light Industries, USA)and Bradly J. Alicea (OpenWorm, USA)
Copyright: 2017
Pages: 37
Source title:
Multi-Agent-Based Simulations Applied to Biological and Environmental Systems
Source Author(s)/Editor(s): Diana Francisca Adamatti (Universidade Federal do Rio Grande, Brazil)
DOI: 10.4018/978-1-5225-1756-6.ch003
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Abstract
A cellular automaton model, Morphozoic, is presented. Morphozoic may be used to investigate the computational power of morphogenetic fields to foster the development of structures and cell differentiation. The term morphogenetic field is used here to describe a generalized abstraction: a cell signals information about its state to its environment and is able to sense and act on signals from nested neighborhood of cells that can represent local to global morphogenetic effects. Neighborhood signals are compacted into aggregated quantities, capping the amount of information exchanged: signals from smaller, more local neighborhoods are thus more finely discriminated, while those from larger, more global neighborhoods are less so. An assembly of cells can thus cooperate to generate spatial and temporal structure. Morphozoic was found to be robust and noise tolerant. Applications of Morphozoic presented here include: 1) Conway's Game of Life, 2) Cell regeneration, 3) Evolution of a gastrulation-like sequence, 4) Neuron pathfinding, and 5) Turing's reaction-diffusion morphogenesis.
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