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MARIA LA GENNUSA

Multi-Agent Systems as Effective Tools for the User-Based Thermal Comfort: an Introduction

  • Autori: La Gennusa, M; Marino, C; Nucara, A; Pietrafesa, M; Pudano, A; Scaccianoce, G
  • Anno di pubblicazione: 2010
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • Parole Chiave: Indoor thermal comfort; Holistic comfort; User behaviour; Adaptative subjective approach; lntelligent agents
  • OA Link: http://hdl.handle.net/10447/57797

Abstract

Through the paper the characterization of a comfort model, enriching that proposed by Fanger with an adaptive approach, is carried out using a Multi Agent System (MAS). This is a well suited coordinated set of Intelligent Agents, that are software applications interacting in order to follow user in his own needs and preferences in relation to indoor comfort, adapting to the changes of context variables. As a matter of fact, MAS are systems aware of the scenery where users live, following them in their own needs and preferences and adapting to their expectations. Indeed, thermal comfort conditions in the built environment are strictly related not only to the thermal and geometric building features and to air-conditioning systems, but also to the building using profile and to the biological-metabolic-psychological characteristics of the users. Within this frame, as a consequence, it is very useful to formalize new models, both subjective and adaptive to the environmental scenery, where users are represented as an integral part of the global experience context, in a particular holistic vision of the problem, strongly addressed towards the personalization of the service, with regards to the novel tern user-plant-building system. In this aim, Intelligent Agents can be considered as the best solution to be adopted, allowing characterization of a control model for an Advanced Smart Conditioning System, that would realize integration of Fanger’s theory with an adaptive approach, also proposed by other authors (Brager and de Dear, Nicols, etc.), in particular by means of a Multi Agent System (MAS).