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Extended Cognition and the Dynamics of Algorithmic Skills.

By: Pinna, Simone.
Material type: TextTextSeries: eBooks on Demand.Studies in Applied Philosophy, Epistemology and Rational Ethics: Publisher: Cham : Springer International Publishing, 2017Copyright date: ©2017Description: 1 online resource (142 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9783319518411.Subject(s): ConsciousnessGenre/Form: Electronic books.Additional physical formats: Print version:: Extended Cognition and the Dynamics of Algorithmic SkillsDDC classification: 004.0151 Online resources: Click here to view this ebook.
Contents:
Foreword -- From Turing Machines to the Dynamical Explanation of Algorithmic Skills -- Acknowledgements -- Contents -- Acronyms -- Introduction -- Outline of the Work -- 1 Turing's Theory of Computation -- 1.1 Turing Machine: Architecture and Functioning -- 1.1.1 Architecture -- 1.1.2 Some Examples of Turing Machines -- 1.2 The Aim of Turing's 1936 Work -- 1.3 The Classic-Computationalist Interpretation of the Turing Machine -- 1.4 The Ecological Interpretation of the TM's Architecture (Andrew Wells) -- References -- 2 Cognition as Organism-Environment Interaction -- 2.1 Active Externalism -- 2.2 Ontological Versus Functional-Explanatory Issues -- 2.2.1 The Ontological Question -- 2.2.2 The Functional-Explanatory Question -- 2.3 The Cognitive Value of the TM -- 2.3.1 Arguments Against the Computational Theory of Mind -- 2.3.2 Neural Networks as Finite Automata -- 2.3.3 Advantages and Disadvantages of the Turing Machine -- 2.4 A Model for Gibson's Concept of Affordance -- 2.4.1 Formal Models of Affordance -- 2.4.2 Affordances and Effectivities as Quintuples of a TM -- References -- 3 Ecological Approach and Dynamical Approach -- 3.1 Cognitive Systems as Dynamical Systems -- 3.1.1 Lines of Investigation -- 3.1.2 Philosophical Issues -- 3.1.3 Dynamical Approach Versus Classic Computationalism -- 3.2 Turing Machines as Dynamical Models -- 3.2.1 Dynamical Systems -- 3.2.2 Components and Basic Operations of the Turing Machine -- References -- 4 Modeling Algorithmic Skills: The Bidimensional Turing Machine -- 4.1 A TM-Inspired Model of Computational Skills -- 4.1.1 Definitions -- 4.2 Two Examples of BTM -- 4.2.1 BTM1 (Counting-All Strategy) -- 4.2.2 BTM2 (Counting Objects on a Grid) -- 4.3 Algorithms, Empirical Models, and Galilean Models -- 4.3.1 Algorithmic Skills -- 4.3.2 Empirical Interpretations.
4.3.3 A Possible Galilean Model of Algorithmic Skills -- References -- 5 BTM Models of Algorithmic Skills -- 5.1 Core Systems Approach -- 5.1.1 Nativism -- 5.1.2 Constructivism -- 5.2 Numerical Skills and Space Representation -- 5.2.1 Ordering Numbers in Space -- 5.2.2 Space and Algorithmic Execution -- 5.2.3 Different Cognitive Contributions -- 5.3 Algorithmic Performance and the Development of Numerical Abilities -- 5.3.1 A Method of Investigation -- 5.3.2 From Simple to Complex Strategies -- 5.3.3 Single-Digit Addition: Two Algorithms of Decreasing Complexity -- 5.3.4 Comparison Between Algorithms -- 5.4 External and Internal Resources -- 5.4.1 Working Memory and Algorithmic Skills -- 5.4.2 BTM5: The Column Algorithm for Addition -- 5.4.3 Model Analysis -- 5.5 Mental Versus External Strategies -- 5.5.1 BTM6: A Mental Algorithm for Multi-digit Additions -- 5.5.2 BTM7: Mental Column-Based Addition -- 5.5.3 BTM6 and BTM7: Comparison of Models -- 5.6 From Cognitive to Subcognitive Skills: A Neural Net Simulation -- 5.6.1 Finger Counting -- 5.6.2 BTM8: Finger Counting Procedure -- 5.6.3 A Neural Net for Performing SDAs -- 5.6.4 Problem-Size Effect -- References -- Conclusion -- Partial Results -- Further Lines of Investigation -- Reference.
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Electronic Book UT Tyler Online
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Foreword -- From Turing Machines to the Dynamical Explanation of Algorithmic Skills -- Acknowledgements -- Contents -- Acronyms -- Introduction -- Outline of the Work -- 1 Turing's Theory of Computation -- 1.1 Turing Machine: Architecture and Functioning -- 1.1.1 Architecture -- 1.1.2 Some Examples of Turing Machines -- 1.2 The Aim of Turing's 1936 Work -- 1.3 The Classic-Computationalist Interpretation of the Turing Machine -- 1.4 The Ecological Interpretation of the TM's Architecture (Andrew Wells) -- References -- 2 Cognition as Organism-Environment Interaction -- 2.1 Active Externalism -- 2.2 Ontological Versus Functional-Explanatory Issues -- 2.2.1 The Ontological Question -- 2.2.2 The Functional-Explanatory Question -- 2.3 The Cognitive Value of the TM -- 2.3.1 Arguments Against the Computational Theory of Mind -- 2.3.2 Neural Networks as Finite Automata -- 2.3.3 Advantages and Disadvantages of the Turing Machine -- 2.4 A Model for Gibson's Concept of Affordance -- 2.4.1 Formal Models of Affordance -- 2.4.2 Affordances and Effectivities as Quintuples of a TM -- References -- 3 Ecological Approach and Dynamical Approach -- 3.1 Cognitive Systems as Dynamical Systems -- 3.1.1 Lines of Investigation -- 3.1.2 Philosophical Issues -- 3.1.3 Dynamical Approach Versus Classic Computationalism -- 3.2 Turing Machines as Dynamical Models -- 3.2.1 Dynamical Systems -- 3.2.2 Components and Basic Operations of the Turing Machine -- References -- 4 Modeling Algorithmic Skills: The Bidimensional Turing Machine -- 4.1 A TM-Inspired Model of Computational Skills -- 4.1.1 Definitions -- 4.2 Two Examples of BTM -- 4.2.1 BTM1 (Counting-All Strategy) -- 4.2.2 BTM2 (Counting Objects on a Grid) -- 4.3 Algorithms, Empirical Models, and Galilean Models -- 4.3.1 Algorithmic Skills -- 4.3.2 Empirical Interpretations.

4.3.3 A Possible Galilean Model of Algorithmic Skills -- References -- 5 BTM Models of Algorithmic Skills -- 5.1 Core Systems Approach -- 5.1.1 Nativism -- 5.1.2 Constructivism -- 5.2 Numerical Skills and Space Representation -- 5.2.1 Ordering Numbers in Space -- 5.2.2 Space and Algorithmic Execution -- 5.2.3 Different Cognitive Contributions -- 5.3 Algorithmic Performance and the Development of Numerical Abilities -- 5.3.1 A Method of Investigation -- 5.3.2 From Simple to Complex Strategies -- 5.3.3 Single-Digit Addition: Two Algorithms of Decreasing Complexity -- 5.3.4 Comparison Between Algorithms -- 5.4 External and Internal Resources -- 5.4.1 Working Memory and Algorithmic Skills -- 5.4.2 BTM5: The Column Algorithm for Addition -- 5.4.3 Model Analysis -- 5.5 Mental Versus External Strategies -- 5.5.1 BTM6: A Mental Algorithm for Multi-digit Additions -- 5.5.2 BTM7: Mental Column-Based Addition -- 5.5.3 BTM6 and BTM7: Comparison of Models -- 5.6 From Cognitive to Subcognitive Skills: A Neural Net Simulation -- 5.6.1 Finger Counting -- 5.6.2 BTM8: Finger Counting Procedure -- 5.6.3 A Neural Net for Performing SDAs -- 5.6.4 Problem-Size Effect -- References -- Conclusion -- Partial Results -- Further Lines of Investigation -- Reference.

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