Complexes

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 to an absolute minimum, we are able to illustrate how the coupling-constitution fallacy is in fact based on an inadequate understanding of the constitutive role of nonlinear interactions in dynamical systems theory.


The Dynamically Extended Mind -- A Minimal Modeling Case Study
Tom Froese, Carlos Gershenson, David A. Rosenblueth
Accepted in Congress on Evolutionary Computation IEEE CEC 2013, Evolutionary Robotics track
http://arxiv.org/abs/1305.1958

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.

Last week Coursera, the leading MOOC (massive open online course) initiative, announced 29 new partners, including UNAM, which will start the partnership giving three courses in Spanish. I have the privilege to teach one of these, on Scientific Thinking. You can already sign up, course begins on May 6th. In less than a week, almost 2500 students have enrolled.