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This book describes a novel methodology for studying algorithmic
skills, intended as cognitive activities related to rule-based
symbolic transformation, and argues that some human computational
abilities may be interpreted and analyzed as genuine examples of
extended cognition. It shows that the performance of these
abilities relies not only on innate neurocognitive systems or
language-related skills, but also on external tools and general
agent-environment interactions. Further, it asserts that a
low-level analysis, based on a set of core neurocognitive systems
linking numbers and language, is not sufficient to explain some
specific forms of high-level numerical skills, like those involved
in algorithm execution. To this end, it reports on the design of a
cognitive architecture for modeling all the relevant features
involved in the execution of algorithmic strategies, including
external tools, such as paper and pencils. The first part of the
book discusses the philosophical premises for endorsing and
justifying a position in philosophy of mind that links a modified
form of computationalism with some recent theoretical and
scientific developments, like those introduced by the so-called
dynamical approach to cognition. The second part is dedicated to
the description of a Turing-machine-inspired cognitive
architecture, expressly designed to formalize all kinds of
algorithmic strategies.
This book describes a novel methodology for studying algorithmic
skills, intended as cognitive activities related to rule-based
symbolic transformation, and argues that some human computational
abilities may be interpreted and analyzed as genuine examples of
extended cognition. It shows that the performance of these
abilities relies not only on innate neurocognitive systems or
language-related skills, but also on external tools and general
agent-environment interactions. Further, it asserts that a
low-level analysis, based on a set of core neurocognitive systems
linking numbers and language, is not sufficient to explain some
specific forms of high-level numerical skills, like those involved
in algorithm execution. To this end, it reports on the design of a
cognitive architecture for modeling all the relevant features
involved in the execution of algorithmic strategies, including
external tools, such as paper and pencils. The first part of the
book discusses the philosophical premises for endorsing and
justifying a position in philosophy of mind that links a modified
form of computationalism with some recent theoretical and
scientific developments, like those introduced by the so-called
dynamical approach to cognition. The second part is dedicated to
the description of a Turing-machine-inspired cognitive
architecture, expressly designed to formalize all kinds of
algorithmic strategies.
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