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in english | suomeksi about – lectures – models – simulation – report151 – publications – links – guestbook about neocybernetics by heikki hyötyniemi in finnish: enformaatioseminaari jyväskylän yliopistolla la 9.3.2013 -- enformaatioteoria (2013) ja mentaalivitalismi (2016) tilattavissa kirjakaupoista. enformaatioteoria tilattavissa kirjakaupoista helmi-maaliskuussa -- lisätietoa » -- - - -- introduction to neocybernetics there are (more or less) eternal mysteries facing us: how to reach emergent coordination in agent systems? how to explain biodiversity in nature? how to characterize robustness in natural networks? how to understand the “whirls” in the flow of entropy ? how to define life ? a new approach to complex systems, or neocybernetics , seems to give new intuitions into these all-embracing issues. cybernetic systems are complex systems with emergent behaviors. they are characterized by mutual interactions and feedbacks among lower-level (faster and more numerous) actors, resulting in dynamic structures. the emergence in such systems is manifested as self-organization and self-regulation . the key point in neocybernetics is that the emergent models are studied directly rather than the physical first-principles ones. it turns out that the analysis and synthesis tools are based on multivariate statistical methods . it has been assumed that behaviors in complex systems cannot be analyzed using traditional mathematics: deeply nonlinear and chaotic models are needed. however, when one directly concentrates on the final stochastic patterns, counterintuitively, one can trust on linearity and stability . rather than studying lifeless algebraic relations or hopelessly complex nonlinear iterations at the edge of chaos – the mainstream approaches today in complex systems research – much broader views can be seen around the dynamic, elastic equilibria. it turns out that cybernetic systems are based on higher-order tensions among networked processes. surprisingly, it is control theory that offers the conceptual tools for understanding the behaviors in nature: a cybernetic system implements emergent model-based control of the degrees of freedom of its environment . the rules norbert wiener (1948): “cybernetics, or control and communication in the animal and the machine” interactions and feedback structures among actors result in emergent complex behaviors long history of false interpretations: for example, controlled (communist) economy cybernetics is one of the starting points beyond artificial intelligence and artificial life now – ai strikes back, bringing new flesh to heuristic studies cybernetics offers a nice framework for studies on computationalism basic ideas from reductionism to holism – new functionalities emerge from close interaction and heavy iteration from complexity to cybernetics – dynamics is the mechanism to reach added value in a complex system from control to self-organization – without external manipulation new structures are created from computation to association – rather than studying iteration processes concentrate on underlying patterns from influencing to perceiving – systems are too complex to be controlled – understanding is enough from natural to artificial systems – analysis of “dynamic differentiation” among niches in synthetic ecosystems tools and frameworks system theory understanding abstractions and limits of systems emphasis on model scalability, balance between linearity and nonlinearity tools for capturing essence of dynamic feedback phenomena multivariate statistics determining models for observation data in a consistent way mastering high-dimensional phenomena, finding latent structures key to reach semantics and control the emergent order new languages new concepts are needed to capture complex phenomena new formalisms are needed to functionalize them on the other hand, algorithms can be expressed and analyzed as dynamic systems research blooms technical cybernetics statistical methods applied in soft sensors, sensor fusion, and calibration emergence of behaviors applied in parameter optimization of industrial systems idea of “fractal robustness” applied in redesign and analysis of a power plant grid natural cybernetics systems biology, modeling of genetic and metabolic systems using dynamic models biodiversity in ecologies and economies, and estimating their qualitative behaviors structured models for neural and cognitive systems, and new languages for them -- explore 12+3 lectures on video – accompanied with transcriptions in finnish, and a few hundred slides illustration of emergent linear models – java applet and animations simulation of neocybernetic ecosystems – java applet research report on neocybernetics (2006) – 283 pages second report on neocybernetics (2013): enformation theory – 244 pages third report on neocybernetics (2016): mental vitalism – 324 pages other publications on neocybernetics – from 1998 to present neocybernetics links – locations, networks, and topics of interest guestbook in brief “ i think that cybernetics is the biggest bite out of the fruit of the tree of knowledge that mankind has taken in the last 2000 years. but most such bites out of the apple have proven to be rather indigestible – usually for cybernetic reasons. ” — gregory bateson. “from versailles to cybernetics”, 1966. in steps to an ecology of mind: collected essays in anthropology, psychiatry, evolution, and epistemology. university of chicago press, 1972. “ as ontological theater, then, a multihomeostat setup stages for us a vision of the world in which fluid and dynamic entities evolve together in a decentered fashion, exploring each other's properties in a performative back-and-forth dance of agency. ” — andrew pickering. cybernetic brain: sketches for another future. university of chicago press, 2010. p.106. -- lectures on elementary cybernetics by heikki hyötyniemi are licensed under a creative commons attribution-noncommercial-share alike 3.0 unported license .

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http://neocybernetics.com/report151/
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