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Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Über Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

This book provides a new perspective on emotion in artificial systems. It presents an insightful explanation of how emotion might emerge deep inside the systems, and emotional behaviour could be seen as a consequence of their internal management. The final approach attempts to account for a range of events associated with emotion, from functional and behavioural features to aspects related to the dynamics and the development of feeling. The book provides a theoretical foundation for engineering and designing computational emotion as a framework for developing future adaptive systems. It includes a painstaking analysis of the rationales for the features of the final approach, including aspects from the fields of Artificial Intelligence, Psychology, the Cognitive Sciences and Model-based Systems. Synthesizing knowledge from a variety of disciplines, it ultimately presents a model conceptualization following the perspectives of Engineering and the Cognitive Sciences.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783319594293
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 258
  • Veröffentlicht:
  • 5. Juli 2017
  • Ausgabe:
  • 12018
  • Gewicht:
  • 5443 g.
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Beschreibung von Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

This book provides a new perspective on emotion in artificial systems. It presents an insightful explanation of how emotion might emerge deep inside the systems, and emotional behaviour could be seen as a consequence of their internal management. The final approach attempts to account for a range of events associated with emotion, from functional and behavioural features to aspects related to the dynamics and the development of feeling. The book provides a theoretical foundation for engineering and designing computational emotion as a framework for developing future adaptive systems. It includes a painstaking analysis of the rationales for the features of the final approach, including aspects from the fields of Artificial Intelligence, Psychology, the Cognitive Sciences and Model-based Systems. Synthesizing knowledge from a variety of disciplines, it ultimately presents a model conceptualization following the perspectives of Engineering and the Cognitive Sciences.

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