Affective computing
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces-Volume I - Volume I
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A user-independent real-time emotion recognition system for software agents in domestic environments
Engineering Applications of Artificial Intelligence
Emotion Recognition and Synthesis System on Speech
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
What planner for ambient intelligence applications?
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Health-status monitoring through analysis of behavioral patterns
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An interactive space that learns to influence human behavior
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Control and learning of ambience by an intelligent building
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Human expression recognition from motion using a radial basis function network architecture
IEEE Transactions on Neural Networks
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The evidence suggests that human actions are supported by emotional elements that complement logic inference in our decision-making processes. In this paper an exploratory study is presented providing initial evidence of the positive effects of emotional information on the ability of intelligent agents to create better models of user actions inside smart-homes. Preliminary results suggest that an agent incorporating valence-based emotional data into its input array can model user behaviour in a more accurate way than agents using no emotion-based data or raw data based on physiological changes.