Polani, Daniel, Mikhail Prokopenko, and Larry S. Yaeger. “Information and self-organization of behavior.” Advances in Complex Systems 16, no. 2&3 (2013): 1303001.
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The goal of Guided Self-Organization (GSO) is to leverage the strengths of selforganization while still being able to direct the outcome of the self-organizing process. GSO typically has the following features: (i) an increase in organization (structure and/or functionality) over some time; (ii) the local interactions are not explicitly guided by any external agent; and (iii) task-independent objectives are combined with task-dependent constraints. Over the last few years a mathematical framework has started to form around these features, promising to provide common organizational and guidance principles across multiple scales and contexts. This process is far from being complete, and every year an International GSO Workshop showcases new breakthroughs that diversify and reshape the field. Nevertheless, some themes and ideas withstand the test of time, maintaining the core of the GSO research.