TL;DR
This paper discusses the multifaceted nature of complexity, highlighting that it lacks a single definition and varies across contexts, encompassing information content, computational effort, and modeling approaches.
Contribution
It provides an overview of different interpretations of complexity, emphasizing its contextual and multi-dimensional aspects.
Findings
Complexity has multiple definitions depending on context.
It can be measured by information content, computational effort, or modeling minimality.
No single universal definition of complexity exists.
Abstract
There is no single definition of complexity (Edmonds 1999; Gershenson 2008; Mitchell 2009; De Domenico, et al., 2019), as it acquires different meanings in different contexts. A general notion is the amount of information required to describe a phenomenon (Prokopenko, et al. 2008) , but it can also be understood as the length of the shortest program required to compute that description, as the time required to compute that description, as the minimal model to statistically describe a phenomenon, etc.
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Taxonomy
TopicsChaos, Complexity, and Education · Benford’s Law and Fraud Detection · Computability, Logic, AI Algorithms