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COGNITION AND COMPUTATION

RSL-IJCS 2017

URL: https://www.mulino.it/riviste/a/issn/2279-7777/newsitem/139
Call For Paper Type: SI
H2 Index: 0
Submission Date: 2017-07-31
Notification Date: 2017-10-15

Artificial Intelligence Engineering & Computer Science (General) Cognitive Science

Call for Papers “Cognition and Computation”
Special issue of
Reti, Saperi, Linguaggi. Italian Journal of Cognitive Sciences
https://www.mulino.it/riviste/issn/2279-7777
One of the founding ideas of cognitive science is that cognition is essentially computation. From the very start, many have denied this view, but in recent times computationalism has increasingly come under attack from several different fronts. From a quick glance at the current cognitive science scenario, one comes away with the impression that several of the criticisms raised against the computational view of mind, rather than leading to the abandonment of computationalism altogether, have instead served to advancing it in several respects. The aim of this call is to collect reflections regarding this scenario. The following is a list of challenges to computationalism, by no means exhaustive, which have spawned new research efforts within the computational paradigm.
• Emotion and consciousness are the mental phenomena more often alleged as defeating computational explanations. Seemingly, computations have affectless, flavorless connotations. Yet, the challenge has been taken seriously, and today research domains such as cognitive affective computation, and machine consciousness, have grown remarkably.
• Embodiment and enactivism have been, and are today, the strongest alternatives proposed to the computational view of mind. However, there are several new research directions, within the computational paradigm, that emphasize the embedding of computational systems within physical body structures and their environment, like, for example, in the field of cognitive robotics.
• Predictive theories of the brain, spanning from Bayesian approaches to free-energy principles, are finding increasingly wide audiences. Even if not conceived as radical alternatives to computationalism, it is often argued that these approaches imply a conceptual shift with respect to mainstream computational modeling. However, others hold that several existing computational modeling approaches can be given a natural probabilistic interpretation that is compatible, and enriched, by the recent probabilistic theories of brain and cognition.
• Mechanistic explanations are gaining traction in most special sciences, especially biology and neuroscience. Even if in the early days computation was often seen as the most precise way for explaining mechanisms, the new mechanistic philosophers tend to conceptualize mechanisms in ways that do not require computation. However, a big theoretical effort is currently underway that relates the new notion of mechanism with computation once again.
• Computationalism has often been criticized for relying on concepts borrowed from theoretical computer science, that lose sense when taken out of their original context and applied to foreign realms like the mind. This criticism has been raised, for example, in regard to computable functions, symbols, computation complexity. Actually, recent advances within theoretical computer science may offer new refined concepts that may greatly help cognitive science as well. The notion of computation has itself been the center of deep theoretical reflection. Computational complexity has significantly been advanced, for example, with parameterized complexity theory, something that has been recently applied in cognitive science.
The above suggestions are by no means exhaustive, and explorations of other challenges faced by computationalism today are encouraged.
Invited Contributors
Raúl Arrabales
Mark Blokpoel, Johan Kwisthout, Iris van Rooij and Todd Wareham
Marcello Frixione
Alistair Isaac
Marcin Miłkowski
Vincent Müller
Matthias Scheutz
Roman Yampolskiy
Submissions should adhere to the following guidelines:
Articles should be submitted in blind review format. Please omit any self–identifying information within the abstract and body of the paper. Max length: 35.000 characters (including spaces, references and an abstract of no more than 150 words). Please use the APA citation style for references.
Language: English
Guest Editor: Alessio Plebe
Submissions should be sent via e-mail to: aplebe[at]unime.it
Important dates:
Deadline for submissions: July 31th, 2017
Notification of acceptance: October 15th, 2017

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