Distributing Fuzzy Reasoning through Fuzzy Markup Language: An Application to Ambient Intelligence

Abstract

Fuzzy Markup Language (FML) is a specific-purpose computer language which is emerging as a standard tool for modeling Fuzzy Logic Controllers (FLCs) in a human-readable and hardware-independent way. By means of these features FML allows FLCs designers to define their systems independently from their legacy representations and provides them with a collection of facilities speeding up the whole development process of a fuzzy system. However, besides the hardware independence feature, the XML nature of FMLmakes possible to embed fuzzy reasoning in computing scenarios characterized by high levels of pervasiveness and ubiquity. Through this additional feature, FML technology may efficiently distribute pieces of the global control flow on different devices populating a pervasive environment. In this chapter, FML features are exploited to implement an agent-based framework designed for providing proactive and distributed services in an Ambient Intelligent (AmI) scenario. In particular, FML is combined with a distributed learning strategy for capturing habits of users that live a smart environment and generating an appropriate collection of services satisfying users’ preferences.As will be shown by a case study, the exploitation of FML distributed features simultaneously allows to achieve the relevant advantage of reducing the fuzzy computation effort and providing the most suitable collection of distributed services fulfilling a prefixed objective.KeywordsFuzzy SystemFuzzy RuleMobile AgentFuzzy ControllerFuzzy ReasoningThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.