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2011 | OriginalPaper | Buchkapitel

3. Emergence of Epibraimatics

verfasst von : George Christakos

Erschienen in: Integrative Problem-Solving in a Time of Decadence

Verlag: Springer Netherlands

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Abstract

Two and a half millennia have passed since the “father of medicine” brought people’s attention to the key role of the brain in human affairs. In the footsteps of Hippocrates, the workings of the brain continue to be at the center of twenty-first century cutting-edge research. Epibraimatics emerges as a synthesis of epistemic ideas and principles (Epi) from the broader field of brain sciences (brai) with the goal of developing action-based mathematics (matics) for solving real-world problems under conditions of multisourced uncertainty and composite space–time change. Also, as noted earlier, Epibraimatics assigns considerable weight on the meaning of things. By re-examining the implications of these ideas in the broader IPS context, the above synthesis assigns a meaning to the problem–solution that is conceptually different than the conventional interpretation. In the same spirit, Epibraimatics seeks a relationship between objectivity and interpretivity involving a generative tension between the two. Hence, it is concerned about any factor that could threaten to topple the sensitive balance between objectivity and interpretivity to one side or the other (objective approaches to problem-solving do strip particular moments of phenomenal life of their particularity, and interpretive approaches are biased by the participation of the subject).

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Vorheriges Kapitel Problem-Solving Revisited

Nächstes Kapitel Space–Time and Uncertainty

This includes neurobiology, evolutionary biology neuropsychology, logic, and cognitive science.

The reader may recall (Section 1.1.1) that, broadly speaking epistemology is a theory of knowledge that explores the structures and processes underlying human knowledge.

How exactly this is done mostly remains a mystery, which has generated different views concerning the nature of the “brain–mind” relationship. While most views seem to agree that brain and mind go hand-in-hand, they differ about the specifics of the relationship (whether the mind somehow emerges from the brain, whether brain and mind are the same thing etc.).

Although not exactly the same, the above distinction is probably close to that proposed by Marvin Minsky (1986: 287): “Minds are simply what brains do.”

As it turns out, consciousness is a difficult concept to define. One reason is that its meaning transcends various disciplines, which makes it a major focus of any multidisciplinary approach.

In a sense, Husserl replaced Descartes’ motto “I think, therefore I am” with “I think about something, therefore I am,” meaning that there is always an object of consciousness.

When encountering the different meanings of “intentionality”, one must clarify which one is intended.

“Cybernetics” comes from the Greek word Κυβερνητική, which means “the art of steering”. Plato was the first who used the term to refer to government.

Some thinkers draw a parallel between the mind-brain duality and the wave-particle duality: Just as in quantum physics one talks of a wave of information (that has a probability shape) about a particle’s physical characteristics, so in cognitive science one talks of a mental function of information (probabilistically interpreted) about the brain’s physical activities. Both the wave function and the mental function, unless they are registered in consciousness, are without significance.

Located inside the medial temporal lobe of the cerebral cortex and, hence, is part of the forebrain. Hippocampus plays a major role in short-term memory and spatial navigation.

“Gestalt” is a structure, configuration or pattern of physical, biological or psychological phenomena so integrated as to constitute a functional unit with properties not derivable by the summation of its parts.

Such as intentionality, teleology, and adaptation (Klahr 2000; Harnish2002; and Section 3.2.3).

A metaphor may be useful here. A computer can be described in two distinct yet mutually compatible ways (Cosmides et al. 1992): one way describes the computer hardware, i.e. how the computer components function and interact (electrons flowing through circuits, chip functions etc.); another way describes the software, i.e. programs that the system runs (input information, data representations and structures, algorithms that transform information etc.).

Chapter 7 will deal with the corresponding quantitative operators.

The ultimate best thing that could possibly happen, the acme, the highest stage of development.

Gaussian, triangular, uniform, or even custom-defined probability distributions.

Like the sale of “indulgences”, a sort of certified checks drawn by the Pope on the treasury of merit accumulated by the saints. Buying one enabled the holder to finesses penance and shorten one’s time in Purgatory (Barzun 2000).

That is, it offers an incomplete representation of the system under consideration; see conceptual uncertainty in Section 4.3.2.4.

Simplicity here is meant in the epistemic rather than in the “simplicity of Nature” sense.

This is widely known as the Liar paradox (Barwise and Etchemendy, 1987).

See, also, the metarules of shadow epistemology (Section 1.4.2).

Gödel’s theorem is also known as the incompleteness theorem. G.H. Hardy said that, “if there was not for the incompleteness theorem we should have a mechanical set of rules for the solution of all mathematical problems, and our activities as mathematicians would come to an end.”

Gödel showed that there must always be some undecidable propositions and Turing argued that there is no systematic way for determining whether any given proposition is or is not decidable.

The incompleteness of mathematical reasoning implies that there is an eternally unbridgeable gap between the two: “everyday truth” is a larger concept than “mathematical truth”.

The disastrous effects of radical postmodernism in higher education have been discussed in Chapter 1.

This was a group of scientists-philosophers who formed the so-called “Vienna Circle” in early twentieth century. The best known among them were Moritz Schlick, Otto Neurath, and Rudolph Carnap.

The issue of knowledge reliability and some historical background were first introduced in Chapter 1.

See, also, Section 3.6.4 above.

Appeal to the people.

These consist of a system of computer programs and data structures that approximate brain’s phenomenological operations. The computer processors, e.g., are connected in a manner suggestive of connections between brain neurons, they respond in parallel to a set of input signals given to each, and they are supposed to learn by trial and error.

In a problem’s context, the truth is increasingly approximated by its solution (see the teachings of the Eleatic school in Section 1.1).

Interestingly, an agent must use a biased and imperfect brain to correct and improve its performance.

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Titel: Emergence of Epibraimatics
verfasst von: George Christakos
Verlag: Springer Netherlands
Buch: Integrative Problem-Solving in a Time of Decadence
Print ISBN: 978-90-481-9889-4

Electronic ISBN: 978-90-481-9890-0

Copyright-Jahr: 2011
DOI: https://doi.org/10.1007/978-90-481-9890-0_3