Complexes

Cybernetics and Systems Research (CSR) were developed in the mid-twentieth century, offering the possibility of describing and comparing different phenomena using the same language. The concepts which originated in CSR have spread to practically all disciplines, many now used within the scientific study of complex systems. CSR has the potential to contribute to the solution of relevant problems, but the path towards this goal is not straightforward. This paper summarizes the ideas presented by the authors during a round table in 2012 on the past, present and future of CSR. The Past, Present and Future of Cybernetics and Systems Research Carlos Gershenson, Peter Csermely, Peter Erdi, Helena Knyazeva, Alexander Laszlo http://arxiv.org/abs/1308.6317

The  MIT Center for Collective Intelligence  has developed a collaborative platform, the Climate CoLab , where thousands of people seek collectively solutions for problems related to climate change. The CoLab is running 18 contests  for different categories. We are finalists in the Transportation Efficiency contest with the project " Self-organizing traffic lights ". Being this a collective platform, people have to vote on the projects they prefer. Teams with the most votes for each contest will be invited to present at the  Crowds and Climate Conference at MIT in November. Key implementers will be there. If you would like traffic lights to work better, please share and  vote for our proposal, " Self-organizing traffic lights " (quick registration required). Summary The optimal coordination of traffic lights is an extremely complex problem. Moreover, traffic situations change constantly, demanding everchanging solutions. Most traffic lights ar...

//Please forward to whom may be interested. The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in March, 2014 (with a close deadline!). Candidates should have obtained a PhD degree within the last three years and be under 36 years, both to the date of the beginning of the fellowship. The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy. Interested candidates should send CV and a tentative project (1 paragraph) to cgg-at-unam.mx by Friday, August 2nd.   Full application package should be ready by Monday, August 5 at noon, Mexico City time. Projects can be inspired from:  http://turing.iimas.unam.mx/~cgg/projects.html Postdoctoral fellowships are between one and two years (after renewal). Spanish is not a requisite. Accepted candidates would be working at the Self-organizing Systems Lab ( http://turing.iimas.unam....

The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization 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; (iii) task-independent objectives are combined with task-dependent constraints. A number of attempts have been made to formalize aspects of GSO within information theory, thermodynamics and dynamical systems. However, the lack of a broadly applicable mathematical framework across multiple scales and contexts leaves GSO methodology incomplete. Devising such a framework and identifying common principles of guidance are the main themes of the GSO workshops. Of particular interest are well-founded, but general methods for characterizing GSO systems in a principled way, with the view of ultimately allowing them to be guided...

The extended mind hypothesis has stimulated much interest in cognitive science. However, its core claim, i.e. that the process of cognition can extend beyond the brain via the body and into the environment, has been heavily criticized. A prominent critique of this claim holds that when some part of the world is coupled to a cognitive system this does not necessarily entail that the part is also constitutive of that cognitive system. This critique is known as the "coupling-constitution fallacy". In this paper we respond to this reductionist challenge by using an evolutionary robotics approach to create a minimal model of two acoustically coupled agents. We demonstrate how the interaction process as a whole has properties that cannot be reduced to the contributions of the isolated agents. We also show that the neural dynamics of the coupled agents has formal properties that are inherently impossible for those neural networks in isolation. By keeping the complexity of the model ...

In this chapter review measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization. Homeostasis reflects the stability of a system. Autopoiesis is defined as the ratio between the complexity of a system and the complexity of its environment. The proposed measures can be applied at multiple scales, which can be studied with multi-scale profiles. Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis Nelson Fernandez, Carlos Maldonado, Carlos Gershenson http://arxiv.org/abs/1304.1842

In this chapter, concepts related to information and computation are reviewed in the context of human computation. A brief introduction to information theory and different types of computation is given. Two examples of human computation systems, online social networks and Wikipedia, are used to illustrate how these can be described and compared in terms of information and computation. Full text at  http://arxiv.org/abs/1304.1428 Draft of a chapter to be published in Michelucci, P. (Ed.) Handbook of Human Computation , Springer.