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About this book

Cognitive Science is a discipline that brings together research in natural and artificial systems and this is clearly reflected in the diverse contributions to From Animals to Robots and Back.

In tribute to Aaron Sloman and his pioneering work in Cognitive Science and Artificial Intelligence, the editors have collected a unique collection of cross-disciplinary papers that include work on:

· intelligent robotics;

· philosophy of cognitive science;

· emotional research

· computational vision;

· comparative psychology; and

· human-computer interaction.

Key themes such as the importance of taking an architectural view in approaching cognition, run through the text. Drawing on the expertize of leading international researchers, contemporary debates in the study of natural and artificial cognition are addressed from complementary and contrasting perspectives with key issues being outlined at various levels of abstraction.

From Animals to Robots and Back, will give readers with backgrounds in the study of both natural and artificial cognition an important window on the state of the art in cognitive systems research.

Table of Contents

Frontmatter

2014 | OriginalPaper | Chapter

Chapter 1. Bringing Together Different Pieces to Better Understand Whole Minds

Dean Petters

2014 | OriginalPaper | Chapter

Chapter 2. Aaron Sloman: A Bright Tile in AI’s Mosaic

Margaret A. Boden

2014 | OriginalPaper | Chapter

Chapter 3. Losing Control Within the H-Cogaff Architecture

Dean Petters

2014 | OriginalPaper | Chapter

Chapter 4. Acting on the World: Understanding How Agents Use Information to Guide Their Action

Jackie Chappell

2014 | OriginalPaper | Chapter

Chapter 5. A Proof and Some Representations

Manfred Kerber

2014 | OriginalPaper | Chapter

Chapter 6. What Does It Mean to Have an Architecture?

Brian Logan

2014 | OriginalPaper | Chapter

Chapter 7. Virtual Machines: Nonreductionist Bridges Between the Functional and the Physical

Matthias Scheutz

2014 | OriginalPaper | Chapter

Chapter 8. Building for the Future: Architectures for the Next Generation of Intelligent Robots

Nick Hawes

2014 | OriginalPaper | Chapter

Chapter 9. What Vision Can, Can’t and Should Do

Michael Zillich

2014 | OriginalPaper | Chapter

Chapter 10. The Rocky Road from Hume to Kant: Correlations and Theories in Robots and Animals

Jeremy L. Wyatt

2014 | OriginalPaper | Chapter

Chapter 11. Combining Planning and Action, Lessons from Robots and the Natural World

Jeremy Baxter

2014 | OriginalPaper | Chapter

Chapter 12. Developing Expertise with Objective Knowledge: Motive Generators and Productive Practice

Luc P. Beaudoin

2014 | OriginalPaper | Chapter

Chapter 13. From Cognitive Science to Data Mining: The First Intelligence Amplifier

Tom Khabaza

2014 | OriginalPaper | Chapter

Chapter 14. Modelling User Linguistic Communicative Competences for Individual and Collaborative Learning

Timothy Read, Elena Bárcena

2014 | OriginalPaper | Chapter

Chapter 15. Loop-Closing Semantics

Ian Wright

Backmatter

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