
Contents
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3.1 Computers and intelligence 3.1 Computers and intelligence
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3.2 What is intelligence anyway? 3.2 What is intelligence anyway?
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3.2.1 Early conceptualizations of intelligence 3.2.1 Early conceptualizations of intelligence
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3.2.2 Further differentiations of intelligence 3.2.2 Further differentiations of intelligence
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3.3 Symbolic artificial intelligence and its limitations 3.3 Symbolic artificial intelligence and its limitations
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3.3.1 Symbolic problem solving 3.3.1 Symbolic problem solving
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3.3.2 Symbolic linguistic processing 3.3.2 Symbolic linguistic processing
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3.4 Hard challenges for symbolic processing systems 3.4 Hard challenges for symbolic processing systems
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3.4.1 Symbol grounding problem 3.4.1 Symbol grounding problem
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3.4.2 Frame problem 3.4.2 Frame problem
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3.4.3 Binding problem 3.4.3 Binding problem
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3.5 Neural networks 3.5 Neural networks
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3.6 Embodied intelligence 3.6 Embodied intelligence
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3.6.1 Embodied biological processing 3.6.1 Embodied biological processing
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How frogs distinguish prey from predators How frogs distinguish prey from predators
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How flies know how to maintain a safe distance How flies know how to maintain a safe distance
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Morphological attractors in four-legged locomotion Morphological attractors in four-legged locomotion
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Ants and swarm intelligence Ants and swarm intelligence
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Summary and conclusion Summary and conclusion
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3.6.2 Embodied artificial intelligence 3.6.2 Embodied artificial intelligence
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Sensorimotor interactions and behavior control loops Sensorimotor interactions and behavior control loops
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Subsumption architecture Subsumption architecture
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Behavioral coordination and executive control Behavioral coordination and executive control
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3.6.3 Embodied cognitive agents 3.6.3 Embodied cognitive agents
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3.7 When have we reached artificial, human cognition? 3.7 When have we reached artificial, human cognition?
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3.8 Exercises 3.8 Exercises
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3 Cognition is Embodied
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Published:January 2017
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Abstract
With the motivation to develop computational and algorithmic levels of understanding how the mind comes into being, this chapter considers computer science, artificial intelligence, and cognitive systems perspectives. Questions are addressed, such as what ‘intelligence’ may actually be and how, and when an artificial system may be considered to be intelligent and to have a mind on its own. May it even be alive? Out of these considerations, the chapter derives three fundamental problems for cognitive systems: the symbol grounding problem, the frame problem, and the binding problem. We show that symbol-processing artificial systems cannot solve these problems satisfactorily. Neural networks and embodied systems offer alternatives. Moreover, biological observations and studies with embodied robotic systems imply that behavioral capabilities can foster and facilitate the development of suitably abstracted, symbolic structures. We finally consider Alan Turing’s question “Can machines think?” and emphasize that such machines must at least solve the three considered fundamental cognitive systems problems. The rest of the book addresses how the human brain, equipped with a suitably-structured body and body–brain interface, manages to solve these problems, and thus manages to develop a mind.
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