Investigating the Emergence of Multicellularity Using a Population of Neural Network Agents | Zendy

Ehud Schlessinger | Zendy; Peter J. Bentley | Zendy; R. Beau Lotto | Zendy

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Investigating the Emergence of Multicellularity Using a Population of Neural Network Agents

Author(s) -

Ehud Schlessinger,

Peter J. Bentley,

R. Beau Lotto

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-38990-3

DOI - 10.1007/11844297_72

Subject(s) - multicellular organism , aggregate (composite) , computer science , artificial life , artificial neural network , population , order (exchange) , natural (archaeology) , division of labour , artificial intelligence , biology , economics , paleontology , demography , market economy , biochemistry , materials science , finance , gene , composite material , sociology

This paper expands Mosaic World, an artificial life model, in order to directly test theories on the emergence of multicellular life. Five experiments are conducted and demonstrate that both the presence of predation and accidental aggregation are sufficient conditions for the transition to multicellularity. In addition, it is shown that division of labour is a major benefit for aggregation, and evolves even if aggregates ‘pay' for abilities they do not use. Analysis of evolved results shows multiple parallels to natural systems, such as differentiation in constituent members of an aggregate, and life-like, complex ecosystems.

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