To naturally compute (something like) biology

Area of Science:

• Computational theory
• Complex systems
• Biophysics

Background:

• Current computational models often lack adaptability and robustness.
• Inspiration from natural systems offers potential for more resilient computation.

Purpose of the Study:

• To propose a novel, 'natural' mode of computation.
• To explore computational models inspired by natural phenomena.
• To investigate context-dependent and potentially failing computational processes.

Main Methods:

• Utilizing principles of dissipative structures in computation.
• Applying concepts of hierarchical structures to computational design.
• Analyzing the developmental processes of natural systems for computational insights.

Main Results:

• A framework for computation that acknowledges potential failure over extended operation.
• Demonstration of how computational deployment can vary based on context.
• Insights into the role of developmental processes in computational systems.

Conclusions:

• Natural systems offer valuable paradigms for developing more adaptive and context-aware computation.
• Computation that can fail offers a more realistic and potentially flexible approach.
• Hierarchical and dissipative structures provide a foundation for novel computational architectures.