Emerging patterns in the complexity: Their organization within Systems Science
AK Mukhopadhyay, 2016
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This innovative essay covering frontier areas of science crystallizes research ideas with translational potentials. It begins with a motivation to simplify the complexity by identification of emerging patterns within it. Overarching the properties of self-organization, organization by life and organization of consciousness, the article unfolds what could be the future of science of information leading from signal to information, to knowledge and wisdom, and vice versa, and also delineates the principles of sensor development for robotics. An emerging new psychology has been identified where the psyche could be considered a five-piece structure and process, which has relevance in cell biology where the cellular cognition is dynamically supported by signal networks of downstream informational molecules. The overall map thus constructed is non-reductive, holistic and falls within the ambits of systems science. The model is testable at micro level of systems cell and at macro level of systems brain. It is applicable also at mega level of a self-conscious, mindful and live universe.
- The decision-making complexity stands, connects and operates in between classical linearity and simplicity of consciousness.
- The terrain appears complex because of unidentified operators stratified in layers, their non-observable operations and their interactions. Those have been identified and described.
- Three novel properties of ‘life’ have been described; uncertainty management, holistically symmetry sensing and ‘life’s access to dark energy.
- The spin-offs from the discourse in the paper are a possible science of information and knowledge organization, and research ideas for developing holographic sensors for robotics.
- Operation of consciousness has been connected non-reductively with systems informatics through systems psyche and systems ‘life’.
A complex system is characterized by its qualitatively and quantitatively unpredictable and variable response for a given standard stimulus. The absolute complexity stands between and connects classical linearity and simplicity of consciousness. It begins with the role of information in what we see as quantum puzzles and paradoxes and extends deeper through sub-quantum and sub-sub-quantum nests of nature to consciousness. Through its various checks and balances, openings and closures the complexity, while
dealing with multitude of intentions, maintains the concern and perfection of the systems by its several independent, autonomous and interconnected operations arranged in stratified layers. The complex system has multiple structures at different scales and a number of processes with different temporal dynamics. This leads to generation of multiple characteristics for the systems (Weaver, 1948, Auyang, 1998, Ji, 2012). The systems appear complex because the properties of a number of variables working within it are not yet totally understood. The difficulty in unwinding this complexity lies in proper identification and description of all of its operators, operations, their interaction and stratification. Paul Nurse (2014), taking cue from physical systems pointed out that the answers to queries on many ill-understood functions of cell systems remain in the complexity biology. According to him (Nurse, 2008), not only the information flow, but also the logic circuits are to be looked into, and to be followed by network analysis.
The motivation to write this paper was to identify and classify the non-observable operations into different groups, understand their connectivity according to the purpose they serve, catalogue those on priority and finally segregate the operations in layers with sole objective of simplifying the issues. As we walk the talk we would see that the novel outcomes of this paper are (i) the future of the science of information leading from signal to information, to knowledge, to wisdom and vice versa (ii) crystallization of the principles of sensor development for robotics (iii) surfacing of an emerging new psychology, where the psyche could be considered a five-piece polylithic structure and process, with its (iv) relevance in cell psychology and cell biology, which is dynamically supported by signal networks of downstream informational molecules. (v) Finally, we draw an overarching non-reductive, holistic map that brings consciousness, self, life and mind and information within the ambits of systems science.
2. Layers of complexity in systems science
The complexity is spread all over the systems science. Systems chemistry and systems physics are amalgamated in systems biology; a courtesy from systems informatics. Systems informatics is connected with systems psychology and systems consciousness. This paper identifies three broad layers in the complexity consisting of a ground, the fabrics and the embroidery. The ground is a supportive and participating ground with a holographic sensor of a dynamically self-renewing wisdom, the crystallized knowledge within consciousness. The fabrics are constituted by the stratified labyrinth of hierarchically nested several independent autonomous operations of information, mind, self and life. [It is interesting to note here Christian de Duve’s opinion on ‘life’. “Life and mind emerge not as by some freak accident, but as a natural manifestation of tendencies in matter written in the fabric of the Universe” (Duve, 1995). We would be working on what could be this fabric of this mindful and live universe? And, what are these tendencies in matter?]. Embroider on the fabrics are constituted by the signal networks of informational molecules of systems chemistry embedded within systems biology. In our journey from the known to the unknown besides wading through existing knowledge we will look into informatics of self-organization, organization by life and organization by consciousness with introduction of several novel ideas.
2.1. Informatics of Self-organization
In the most surface layer of complexity there is self-organizing systems where the entire creation is maintained autonomously without a creator attending to its details. Self-organization has been described in both non-living and living state and we will see that it has never achieved the desirable level of perfection without life. What make self-organization apparently autonomous are its efficient informatics; signal network, logic modules and a sensor with global focus. The operations are distributed over three layers, as shown in Table 1, as layer A, B and C run respectively by the currency of signal, digital information and non-digital information. Layer A deals with flow of signals. Layer B is having the logic modules on the basis of which flow operates, and the layer C as the global sensor is engaged in network analysis. Three layers are nested one over the other. There are recent publications in cell biology with a message that mere information flow is not sufficient for understanding the complexity at the micro level of a cell. The logic behind such flow is far more important (Ortega and van der Donk, 2016). Layers A and B have their own spatio-temporal dynamics, mono-planer or multi-planner, while network analysis in the Layer C is more global in its approach and in operation.