It is in the flux of the PresentNow that our cells must guarantee, in the FutureNow, the sustainability that guarantees our permanence as living systems. But what is this FutureNow?! What does it mean, as a word?! We are always a to being (verb). We must “replicate” in the future our “material” conditions of presence, if we do not guarantee that, we cannot survive.
The “future” is our position in the “flux” of permanence: we have to be before ourselves to be in ourselves, we must anticipate in the “flux” our presence in the permanence of ourselves, and this is our “afterness”: we, each of us, are after ourselves.
We must enact ourselves, we must enact the permanence of ourselves in ourselves: that is selfsustainability, that is autopoietics.
There is always dissipation, because of that we must manage(ing) the losses of integrity to maintain ourselves as presence, but all this is a (co)simultaneity, because the future is a “tag”, because all these are dynamics and rhythms that take place simultaneously.
From the complex sciences’ scientific basis, quantum complex systems science may offer new conceptual and modeling tools to address risk in complex systems, including human societies and economies.
In order to be effective, quantum complex systems science must generalize formalisms, tools and methodologies to be able to apply them effectively in different settings. Thus, from the underlying formalism of quantum mechanics, one may develop interdisciplinary work and apply it to different problems which are of concern to the complex systems sciences and to risk science.
A few examples of research centers directly concerned with complex quantum systems include:
The abovequoted first research center works within the BrusselsAustin school for complexity, mainly influenced by Prigogine’s work and has a theoretical background that is strongly integrated with the conceptual basis of risk science.
Combining the BrusselsAustin approach with risk science, the dynamics of complex systems can be approached as a game of survival, such that complex systems need to expose themselves to risk situations, consuming resources and enacting adaptive dynamics towards the systemic sustainability, dynamics which are, themselves, generative of risk situations.
This conceptual basis for risk and complex systems’ dynamics results from the notion of dissipative structure, introduced by Prigogine, within thermodynamics: a dissipative structure is an open system that feeds on energy and matter from the environment and dissipates heat as a way to sustain its systemic activity.
Conceptually, the notion of dissipative structure synthesizes a dynamics of survival, linked to processes of (eco)systemic management towards an adaptive sustainability in a permanent game of aggregation and disaggregation.
Combining the systemic thinking of Varela with Prigogine’s, one can address the notion of dissipative structure as a system whose autopoietic dynamics leads it to the survival far from a systemic regime of structural dissolution in a disaggregating flux (selforganization far from the thermodynamic equilibrium).
From the standpoint of risk science, a dissipative structure can be addressed in terms of a notion of risking structure, such that complex systems, worked from this notion, can be considered as enactors of systemic risk as an adaptive survival response when placed before permanent threats of disaggregating dissolution.
The dissipative structures/risking structures’ selforganizing processes constitute examples of adaptive processes related to a systemic struggle for survival, approached, within the BrusselsAustin School, from a notion of sustainability against a disaggregating flux, thus, these structures constitute examples of the notion of complex adaptive system, worked upon the Santa Fe Institute.
Quantum complex systems science can help address a general approach to risk and dynamics of complex adaptive systems whenever a mathematical approach is needed to incorporate the following elements:
a) Discrete state variables and continuous state averages with complex dynamical behavior (including (noisy) chaos);
b) Adaptive computation of risk;
c) Multiple intercoupled dynamics with different degrees of freedom;
d) Fluctuating population numbers;
e) Interacting adaptive fields on networks with quantized state variables.
The above elements make effective the usage of the mathematical formalism of quantum mechanics made available to interdisciplinary work through quantum game theory and, in the case of economics, through econophysics.
Application to Economics
In the video below is an example of a model from a work that implements an application of quantum complex systems science and risk science to complex economic dynamics modeling.
The model, also available at Netlogo Commons (http://bit.ly/wyiWYc), is introduced in the article "Chaos and Nonlinear Dynamics in a Quantum Artificial Economy" arXiv:1202.6647v1[nlin.CD] (http://arxiv.org/abs/1202.6647) and it constitutes an example of how quantum complex systems science can be applied to economics.
In most businesses, one deals with discrete business volumes (or in the case of companies that supply goods: discrete quantities), thus, to address economic chaotic dynamics one may, effectively, assume some quantization scheme of fundamental economic variables and economic equilibrium conditions, working with a business game process, in which the quantum averages, from transaction round to transaction roundm follow the continuous state classical chaotic dynamics of some (coupled) nonlinear map.
The work builds up on such a proposal, introducing a quantum artificial economy with (quantum) chaotic dynamics, by combining quantum game theory, quantum chaos theory and coherent state lattice field solutions.
At each transaction round, each company is characterized by a coherent state solution for the business volume (measured in quantities), which corresponds to a quantum business game equilibrium condition.
The nonlinear map introduces an adaptive walk on a hypercubic lattice, implementing a business' quantum economics version of Kaneko's selforganizing genetic algorithms. In this way, each company's binary string code corresponds to a core business strategic profile, where each bit of the binary string is a core business dimension (among core business dimensions one can include the mission statement and business concept).
The coupled quadratic map implements four types of evolutionary dynamics:
(A)  Local competition dynamics between companies that are close to each other in their core business strategic dimensions (local hypercubic lattice onebit mutant neighors' coupling as per Kaneko's proposal of selforganizing genetic algorithms);
(B)  Global competitiveness' industrywide evolutionary race;
(C)  Market share feedback effects upon a business fitness (this leads to a coupling between the quadratic map and the previous transaction round's company's market share, such that the previous round's quantum fluctuations affect the company's fitness dynamics).
(D)  Local fitness dynamics given by the quadratic map with nonlinearity parameter b.
Quantum chaos is a third approach to modeling economic nonlinear dynamics that can be added to the nonlinear deterministic and nonlinear deterministic plus noise modeling family of economic chaos. By addressing evolutionary quantum strategies one is not dealing with a plus noise approach but, instead, with an evolutionary systemic dynamics where probability distributions and chaotic dynamics are interconnected with risk cognition and business adaptive processes, thus, deepening the conceptual grounding on complex adaptive systems science and quantum complex systems science.
Probabilis, probatio, probo are three Latin words that form a judicative entanglement committed, always, with a sense of judgment, plausibility, proof, verification and argumentation.
Probability, as a notion, is an evaluative cognitive synthesis about events, facts, situations, processes, contexts, future(s)...
The probability does not have an ontologically postulable algorithmic nature, the probability depends, always, upon the data, supplied by the systemic sustainability towards the event, the fact, the situation, etc...,
There is no such thing as a probabilistic dynamics, that is nonsense, the referent is the cognitive dynamics: in fundamental terms, the socalled “probabilistic dynamics” is a cognitive dynamics, depending upon the cognitive processing of the data supplied by the intensity of the systemic sustainability for an event to take place, sustainability which, in turn, depends upon some kairosean coincidence, that is, depends upon, until the last moment, there not taking place something unexpected that makes the system deviate itself from that which would become its trajective choice.
The sustainability is enacted by the system, from its own game of survival, a game that involves a web of players..., and just when the game wins such a sustainability that makes visible to all the players what the outcome will be, (oh no!‼) one of the players chokes, the cards are all exposed for everyone to see and the game ends not as it would.
The probability is not an operator of anything. The sustainability of the systems is the operator that guarantees, in the FutureNow, the flux that sustains the present moment that follows the present moment,..., and we, humans, with a very precarious desiring cognitive device, will have to make a serious effort to, in a here and now, guarantee the projective sustainability, so that a FutureNow guarantees us the next present moment. What is the role of the probability in this case?! Just a valorative cognitive synthesis that helps us decide.
In the end, the greater game is between the system’s sustainability and the systemic spontaneity itself. The Latin has, for the term spontaneity, a very interesting cognitive support: spontaneous is primitively radiculated in sponte from spons, mea/tua/sua sponte, which means: by my/your/its will/arbitriu.
No one imposes the system anything, no probabilistic delirium imposes whatever. The system, each system, has its own spontaneous/immediate survival responses in the evolutionary game of survival.
There is no ProbabilityField, there is survival, there are games..., also games of power: to can be, to can do, in the end, to can to survive, either competing, either cooperating. The probability judgment always depends upon the processing of data and it is always subjective/intersubjective.
The system does not show everything, the system does not show all its cards, and it waits for the opportunities to emerge, always hoping that the IntersystemicClinamenic does not become unfavorable..., and this is about risk, and this is about living, dying, and also about dignity, of course.
Topos: o lugar das coisas, o lugar de cada coisa.

Por: Maria Odete Madeira
Topos é o termo primitivo grego para lugar, não um lugar para as coisas mas
o lugar das coisas, de cada coisa, a saber: a sua ex...