Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
How smart are our environments? An updated look at the state of the art
Pervasive and Mobile Computing
The WM method completed: a flexible fuzzy system approach to data mining
IEEE Transactions on Fuzzy Systems
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In intelligent inhabited environments(IIEs), the different user's preferences and needs are different, and the same user's preferences will change over time, which desire that the intelligent agents have evolvement function. In this paper, we propose a new fuzzy control system that is embedded in the intelligent agent which is a function agent in Multi-Agent System(MAS) based on ZigBee wireless sensor network. The system learns the user's preferences according to the manually operation of the user and proactively controls the environment. The intelligent fuzzy agent includes four phases: (1) Capturing inputoutput data pairs. (2) Extracting fuzzy rules. (3) Agent control. (4). Modifying fuzzy rules online. Initially the system's fuzzy rules are extracted from the collected information of sensors and actuators in IIEs, after that the system rapidly optimizes the fuzzy rules when the user's preferences change. The experience results show that the proposed system is effective. Moreover, adding the time and user behaviors inputs will improve the learning accuracy of the system.