Agents that reduce work and information overload
Communications of the ACM
Smart Office: Design of an Intelligent Environment
IEEE Intelligent Systems
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Embedding Computational Intelligence in Pervasive Spaces
IEEE Pervasive Computing
Hybrid computational intelligence for ambient intelligent environments
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
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
Fuzzy cognitive maps for artificial emotions forecasting
Applied Soft Computing
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Ambient Intelligence (AmI) is a pervasive computing paradigm whose main aim is to design smart environments composed of invisible, connected, intelligent and interactive systems, which are naturally sensitive and responsive to the presence of people, providing advanced services for improving the quality of life. Nevertheless, AmI systems are more than a simple integration among computer technologies; indeed, their design can strongly depend upon psychology and social sciences aspects describing, analysing and forecasting the human being status during the system's decision making. This paper introduces a novel methodology for AmI systems designing that exploits a service-oriented architecture whose functionalities are performed by a collection of so-called cognitive agents. These agents exploit a novel extension of Fuzzy Cognitive Maps benefiting on the theory of Timed Automata and a formal method for representing human moods in order to distribute emotional services able to enhance users' comfort and simplify the human/systems interactions. As will be shown in experimental results, where a usability study and a confirmation of expectations test have been performed, the proposed approach maximizes the system's usability in terms of efficiency, accuracy and emotional response.