Quantifying the complexity of a system

AI Thread Summary
The discussion focuses on methods for quantifying the complexity of systems to enable comparison, particularly in computational terms. Participants suggest that while systems like a double pendulum, global climate, and animal brains exhibit varying levels of complexity, there is a need for standardized metrics. Key concepts mentioned include algorithm length and Kolmogorov complexity as potential measures. The conversation also touches on the application of these methods to biological systems, raising questions about how complexity metrics would apply to organisms like bacteria. Overall, there is interest in developing universally accepted frameworks for measuring system complexity.
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Are there generally accepted methods for quantifying the complexity of a system, enabling comparison and the requirements for quantitatively modeling it? Think everyone would agree that in complexity, for example a double pendulum is less complex than the global climate which is in turn less complex than an animal brain, but is there a useful way to quantify this?
 
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More along the lines of computational complexity. one measure would be perhaps the length of the algorithm needed to model it?
 
Yes thanks, does this get used at all on biological systems? Wonder how a bacteria would come out
 
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