Intelligent Fuzzy Agent for Intelligent Inhabited Environments

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 input-output 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.