New Paper: The Dynamically Extended Mind -- A Minimal Modeling Case Study

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

New draft: Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis

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

New Draft: Information and (Human) Computation

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.

Course on Coursera

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.

Improving public transport with a budget

Large cities benefit from public transport. It is simply more efficient to transport hundreds or thousands of people together (trans, trams, buses) than each of them individually (cars, taxis). However, public transportation systems have to match the passenger demand. If there are relatively too few passengers for the public transport capacity, there will be idling and waste of resources. If there are relatively too many passengers, the system will be saturated and become inefficient. This balance between public transport capacity and demand is very tricky, since many cities change their transportation demands much faster than their public transport infrastructure.

There is also a clear correlation between the cost, building time, and capacity of transportation systems. Trains and metros are high cost, high capacity, making them unsuitable for cities of roughtly less than a million inhabitants. Trams and bus rapid transit (BRT) are intermediate: they have less capacity, but they cost less and can be built in less time. These are not only suitable for medium cities, but for routes with medium demands in megacities. The low cost and low capacity end of the spectrum is filled by buses and minibuses. Compared to the high and medium capacity public transportation systems, low capacity transportation systems tend to be slower and less efficient per passenger. It is not possible to build BRT for all transportation routes in cities, there will be much more low demand routes than those that justify the investment of BRT. Can we have some of the benefits of BRT in low capacity transportation systems?

BRT have been very popular because a line can be built in less than a year. Metro lines can take 3-6 years, costing six times more per kilometer. Certainly, metro lines have a higher passenger capacity and average speed than BRT. But BRT are a good option for routes which do no thave the high demand justifying a metro line (or the city budget does not allow for it, better than nothing?). They accelerate transportation over buses because passengers pay when they enter stations, and can enter all at once through several doors when buses arrive at stations. The cost: building stations and the public space for them, along with dedicated lanes. Buses spend much time simply receiving payments from passengers. In Mexico City, some buses even have a dedicated person (commonly underaged) to collect the fares.

It would be too expensive to have dedicated stations for all transportation routes in cities such as Mexico. However, the time lost collecting fares could be considreably reduced with prepaid cards, as it has been done in several cities (e.g. Hong Kong, Brussels, Boston...). In Mexico City, there is a notable lack of coordination between transportation systems. Recently a "city card" was released to pay for metro and BRT. Soon it should be usable for tram lines. We are just changing mayor, who has announced that the chaotic routes of "microbuses" (now transporting more than half of the population) will gradually be transformed into private companies, with benefits for the drivers and passengers. It will be very important that they also integrate the city card to accelerate payments. This will improve the service, reduce traffic, pollution, equal headway instabilities, and even leave digital trails which can be used for different purposes. One option would be to let them accept cash, at least for some time. Just let them charge more for it, to motivate people to get their cards. It is fair, if you use cash, you are delaying everybody in the bus. You should pay for that.

Book chapter published: Facing complexity: Predition vs. adaptation

Gershenson, C. (2013). Facing complexity: Predition vs. adaptation. In A. Massip and A. Bastardas (eds), Complexity Perspectives on Language, Communication and Society.

One of the presuppositions of science since the times of Galileo, Newton, Laplace, and Descartes has been the predictability of the world. This idea has strongly influenced scientific and technological models. However, in recent decades, chaos and complexity have shown that not every phenomenon is predictable, even if it is deterministic. If a problem space is predictable, in theory we can find a solution via optimization. Nevertheless, if a problem space is not predictable, or it changes too fast, very probably optimization will offer obsolete solutions. This occurs often when the immediate solution affects the problem itself. An alternative is found in adaptation. An adaptive system will be able to find by itself new solutions for unforeseen situations.

Video: Las implicaciones de las interacciones para la ciencia y la filosofía

From today's seminar [in Spanish]

http://bambuser.com/v/3140519


Based on:

• Gershenson, C. (In Press) The Implications of Interactions for Science and Philosophy. Foundations of Science. http://dx.doi.org/10.1007/s10699-012-9305-8

Paper published: Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments

In evolutionary biology, attention to the relationship between stochastic organisms and their stochastic environments has leaned towards the adaptability and learning capabilities of the organisms rather than toward the properties of the environment. This article is devoted to the algorithmic aspects of the environment and its interaction with living organisms. We ask whether one may use the fact of the existence of life to establish how far nature is removed from algorithmic randomness. The paper uses a novel approach to behavioral evolutionary questions, using tools drawn from information theory, algorithmic complexity and the thermodynamics of computation to support an intuitive assumption about the near optimal structure of a physical environment that would prove conducive to the evolution and survival of organisms, and sketches the potential of these tools, at present alien to biology, that could be used in the future to address different and deeper questions. We contribute to the discussion of the algorithmic structure of natural environments and provide statistical and computational arguments for the intuitive claim that living systems would not be able to survive in completely unpredictable environments, even if adaptable and equipped with storage and learning capabilities by natural selection (brain memory or DNA).

Zenil, Hector; Gershenson, Carlos; Marshall, James A.R.; Rosenblueth, David A. 2012. "Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments." Entropy 14, no. 11: 2173-2191.

http://www.mdpi.com/1099-4300/14/11/2173

Paper Published: The Implications of Interactions for Science and Philosophy

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions—which reductionism neglects—are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.

The Implications of Interactions for Science and Philosophy

Carlos Gershenson

FOUNDATIONS OF SCIENCE

2012, DOI: 10.1007/s10699-012-9305-8

New draft: Living is information processing; from molecules to global systems

We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: (a) living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; (b) this information processing has one overall function - to perpetuate itself; and (c) the processing method is filtration (cognition) of, and synthesis of, information at lower levels to appear at higher levels in complex systems (emergence). We show how information patterns, are united by the creation of mutual context, generating persistent consequences, to result in `functional information'. This constructive process forms arbitrarily large complexes of information, the combined effects of which include the functions of life. Molecules and simple organisms have already been measured in terms of functional information content; we show how quantification may extended to each level of organisation up to the ecological. In terms of a computer analogy, life is both the data and the program and its biochemical structure is the way the information is embodied. This idea supports the seamless integration of life at all scales with the physical universe.


Living is information processing; from molecules to global systems
Keith D. Farnsworth, John Nelson, Carlos Gershenson
http://arxiv.org/abs/1210.5908