Mechanisms, Symbols, and Models Underlying Cognition: First by José Mira Mira (auth.), José Mira, José R. Álvarez (eds.)

By José Mira Mira (auth.), José Mira, José R. Álvarez (eds.)

The two-volume set LNCS 3561 and LNCS 3562 represent the refereed complaints of the 1st foreign Work-Conference at the interaction among common and synthetic Computation, IWINAC 2005, held in Las Palmas, Canary Islands, Spain in June 2005.

The 118 revised papers offered are thematically divided into volumes; the 1st contains the entire contributions as a rule comparable with the methodological, conceptual, formal, and experimental advancements within the fields of Neurophysiology and cognitive technological know-how. the second one quantity collects the papers comparable with bioinspired programming techniques and the entire contributions comparable with the computational options to engineering difficulties in numerous program domains.

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Additional info for Mechanisms, Symbols, and Models Underlying Cognition: First International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I

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What we have defended in this work is that the CP, understood in the broad and structured sense in which it has been presented here, is a useful epistemological and constructive approximation for understanding neurophysiology and cognition. In other words, the CP is a conceptual and theoretical non-exclusive framework situated above machines and living creatures (two instantiations), sufficiently solid and formalizable to allow us: (1) to ensure that the “facts” (our data) are the relevant facts to which we must pay attention and are not clouded by incorrect statements about the functioning of the nervous system.

1. An interpretation of ’task structures’ - a task with two alternative methods terms) in AI may be inspired from human, monkey or lion biologies, or designed entirely independently from biological models. So, there may be a one-to-many mapping between a particular functionality (of a task) and the corresponding algorithms and their implementations. An AI methodology should describe how this mapping takes place. A significant amount of AI research relies on behavioral sciences as an inspiration source for identification and analysis of a ’task’.

In other words, correspondence between causality at the KL and underlying causalities at the SL and PL is lost. This is the result of thinking of the computer as a general purpose programmable machine, instead of thinking of it as a biological machine which, if we wanted to maintain an analogy with physical machines, we would say that it is a special purpose adaptive machine, whose function is modified as a result of the interactive activity of its mechanisms with the mechanisms of the environment.

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