Anthropic agency: a multiagent system for physiological processes Francesco Amigoni * , Marco Dini, Nicola Gatti, Marco Somalvico Artificial Intelligence and Robotics Project, Dipartimento di Elettronica e Informazione, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano, Italy Received 26 August 2002; received in revised form 18 October 2002; accepted 18 October 2002 Abstract Multiagent systems are powerful and flexible tools for modelling and regulating complex phenomena. In fact, a way to manage the complexity of a phenomenon is to decompose it in such a way that each agent embeds the control model for a portion of the phenomenon. In this perspective, the cooperative interaction among the agents results in the controller for the whole phenomenon. Since the portions in which the phenomenon is decomposed may overlap, the actions the single agents undertake to regulate these portions may conflict; hence a balanced negotiation is required. A class of complex phenomena that present several difficulties in their satisfactory modelling and controlling is the class of physiological processes. The purpose of this paper is to introduce a general multiagent architecture, called anthropic agency , for the modelling and the regulation of complex physiological phenomena. # 2003 Elsevier Science B.V. All rights reserved. Keywords: Physiological process control; Anthropic agency; Negotiation; Glucose–insulin metabolism processes 1. Introduction Multiagent systems [35] are collections of interacting heterogeneous entities, called agents. An agent can be defined as a special kind of physical (computer or robot) or logical (software) entity that presents the properties of autonomy, social ability, reactivity, and pro- activeness [37]. A multiagent system is a recognised powerful and flexible tool for modelling and controlling some complex phenomena, since it can host, within its component agents, the coexistence of multiple partial models of a given phenomenon Artificial Intelligence in Medicine 27 (2003) 305–334 * Corresponding author. Tel.: þ39-02-2399-3475; fax: þ39-02-2399-3411. E-mail address: amigoni@elet.polimi.it (F. Amigoni). 0933-3657/03/$ – see front matter # 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0933-3657(03)00008-3