Originating from biology and later adopted into systems theory and cognitive science, autopoiesis refers to the self-creating and self-maintaining nature of living systems. It emphasizes how these systems can produce the components necessary for their operation and survival, establishing a clear boundary between themselves and their environment. In AI, the concept of autopoiesis has inspired research into developing systems that can adapt, learn, and maintain their integrity in changing environments autonomously. This involves complex interactions between the system's components, requiring sophisticated algorithms that enable self-regulation, adaptation, and evolution, drawing parallels with biological organisms' resilience and adaptability.
Historical Overview: The term autopoiesis was first introduced in 1972 by Chilean biologists Humberto Maturana and Francisco Varela to describe the self-maintaining chemistry of living cells. Its application within AI and cognitive science gained traction in the late 20th century as researchers explored the parallels between biological systems and artificial systems' operational and organizational principles.
Key Contributors: Humberto Maturana and Francisco Varela are the principal figures behind the development of the autopoiesis concept, providing a foundational framework that has influenced fields beyond biology, including psychology, sociology, and artificial intelligence.