Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems (Cognitive Systems Monographs, 33)

Book info: Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems (Cognitive Systems Monographs, 33) (Hardcover, 279 pages) – Springer, 2017. Language: English.

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 CognitiveSciences. Editorial Reviews From the Back Cover 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 CognitiveSciences.