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Paper Published: The Implications of Interactions for Science and Philosophy

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions—which reductionism neglects—are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.


The Implications of Interactions for Science and PhilosophyCarlos Gershenson FOUNDATIONS OF SCIENCE 2012, DOI:10.1007/s10699-012-9305-8
Update 2013-12-09
Finally got its volume number:
Foundations of Science
November 2013, Volume 18, Issue 4, pp 781-790

New draft: Living is information processing; from molecules to global systems

We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: (a) living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; (b) this information processing has one overall function - to perpetuate itself; and (c) the processing method is filtration (cognition) of, and synthesis of, information at lower levels to appear at higher levels in complex systems (emergence). We show how information patterns, are united by the creation of mutual context, generating persistent consequences, to result in `functional information'. This constructive process forms arbitrarily large complexes of information, the combined effects of which include the functions of life. Molecules and simple organisms have already been measured in terms of functional information content; we show how quantific…

Video: Complexity and Information: Measuring Emergence, Self-organization, Homeostasis, and Autopoiesis at Multiple Scales

Complexity and Information: Measuring Emergence, Self-organization, Homeostasis, and Autopoiesis at Multiple Scales

Keynote talk at the 5th International Workshop on Guided Self-Organization. University of Sydney, Australia, September 26th, 2012.



Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. We use information theory to provide abstract and concise measures of complexity, emergence, self-organization, homeostasis, and autopoiesis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self- organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. Autopoiesis can be measured as the ratio between the information pr…

IWSOS 2013 7th International Workshop on Self-Organizing Systems Palma de Mallorca, 9-10th of May, 2013

IWSOS 2013
7th International Workshop on Self-Organizing Systems
Palma de Mallorca, 9-10th of May, 2013
http://ifisc.uib-csic.es/iwsos2013/


IWSOS 2013 is the seventh International Workshop on Self-Organizing Systems, a multidisciplinary event dedicated to self-organization in networks and networked systems, including techno-social systems.

Self-organization relates the behavior of the individual components (the microscopic level) to the resulting networked structure and functionality of the overall system (the macroscopic level), where simple interactions at the microscopic level may already give rise to complex, adaptive, and robust behavior at the macroscopic level. The growing scale, complexity, and dynamics of (future) networked systems have been driving research from centralized solutions to self-organized networked systems. The applicability of well-known self-organizing techniques to specific networks and networked systems is being investigated, as well as adaptations and novel app…