Proceedings:
Architectures for Modeling Emotion: Cross-Disciplinary Foundations
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Papers from the 2004 AAAI Spring Symposium
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Abstract:
I propose a conceptual framework for emotions according to which they are best understood as the feedback mechanism a creature possesses in virtue of its function to learn. More specifically, emotions can be neatly modeled as a measure of harmony in a certain kind of constraint satisfaction problem. This measure can be used as error for weight adjustment (learning) in an unsupervised connectionist network.
Spring
Papers from the 2004 AAAI Spring Symposium