This study addresses the problem of combining insights from artificial life, artificial intelligence, and biology in an efficient way to form a holistic unified view of life and living systems. Today, the study of biological life has a common root object – the cell – although lacking a formal definition of it. The theory of artificial life and artificial intelligence lacks this type of a root object. Here, we present a generalized model of the real biological cell in terms of a framework that is derived from theoretical studies of life. The framework is conceptualized generally as the MIC framework (Metabolism, Information, Compartment). The result is an autopoietic model with generic systemic properties and a network structure that can be examined further from a formal system-theoretic perspective. This study introduces a new way of describing the cell, providing new kind of access to existing biological knowledge of life. It may provide new tools for more efficient utilization of biological data and knowledge in the design and study of artificial life.

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