Anthropic agency: a multiagent system for physiological processes

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.

[1]  N. R. Jennings,et al.  To appear in: Int Journal of Group Decision and Negotiation GDN2000 Keynote Paper Automated Negotiation: Prospects, Methods and Challenges , 2022 .

[2]  Michael Wooldridge,et al.  Agent-based software engineering , 1997, IEE Proc. Softw. Eng..

[3]  C. S. G. Lee,et al.  Robotics: Control, Sensing, Vision, and Intelligence , 1987 .

[4]  Robert W. Brennan,et al.  Dynamic control architecture for metamorphic control of advanced manufacturing systems , 1997, Other Conferences.

[5]  Robert S. Parker,et al.  Advanced model predictive control (MPC) for type I diabetic patient blood glucose control , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[6]  J. V. Rauff,et al.  Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence , 2005 .

[7]  Victor Lesser,et al.  Multistage negotiation in distributed planning , 1988 .

[8]  Franco Zambonelli,et al.  Coordination for Internet Application Development , 1999, Autonomous Agents and Multi-Agent Systems.

[9]  Penny Nii.  The blackboard model of problem solving , 1986 .

[10]  Penny Nii,et al.  Blackboard systems part two: Blackboard application systems , 1986 .

[11]  Francesco Amigoni,et al.  A multiagent interaction paradigm for physiological process control , 2002, AAMAS '02.

[12]  Bruce J. West,et al.  FRACTAL PHYSIOLOGY AND CHAOS IN MEDICINE , 1990 .

[13]  Henry Buchwald,et al.  A new spring-driven implantable drug infusion pump , 1989, Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society,.

[14]  Fabio Balduzzi,et al.  A hybrid software agent model for decentralized control , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[15]  J. Radziuk,et al.  An adaptive plasma glucose controller based on a nonlinear insulin/glucose model , 1994, IEEE Transactions on Biomedical Engineering.

[16]  Ary L. Goldberger,et al.  Chaos in Physiology: Health or Disease? , 1987 .

[17]  P L Miller,et al.  Combining statistical, rule-based, and physiologic model-based methods to assist in the management of diabetes mellitus. , 1990, Computers and biomedical research, an international journal.

[18]  NICHOLAS R. JENNINGS,et al.  An agent-based approach for building complex software systems , 2001, CACM.

[19]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[20]  Jan Eric Larsson,et al.  Guardian: An Intelligent Autonomous Agent for Medical Monitoring and Diagnosis , 1998, IEEE Intell. Syst..

[21]  Francesco Amigoni,et al.  A theoretical framework for the conception of agency , 1999, Int. J. Intell. Syst..

[22]  Julie A. Adams,et al.  Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence , 2001, AI Mag..

[23]  L. Chaudron,et al.  Cooperative decisions and actions in multi-agent worlds , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[24]  Giuseppe Menga,et al.  Designing concurrent and distributed control systems , 1996, CACM.

[25]  Ken Arnold,et al.  The Java Programming Language , 1996 .

[26]  Paul A. Fishwick,et al.  An object-oriented multimodel approach to integrate planning, intelligent control and simulation , 1993, 1993 4th Annual Conference on AI, Simulation and Planning in High Autonomy Systems.

[27]  Giuseppe Menga,et al.  Designing concurrent and distributed control systems : Software patterns , 1996 .

[28]  Alan H. Bond,et al.  Readings in Distributed Artificial Intelligence , 1988 .

[29]  Francesco Amigoni,et al.  A Multilevel Architecture of Creative Dynamic Agency , 2000 .

[30]  E. Salzsieder,et al.  KADIS: model-aided education in type I diabetes. Karlsburg Diabetes Management System. , 1994, Computer methods and programs in biomedicine.

[31]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[32]  H. Penny Nii,et al.  Blackboard systems: the blackboard model of problem solving and the evolution of blackboard architectures , 1995 .

[33]  Lee D. Erman,et al.  Distributed intelligent control and management: concepts, methods and tools for developing DICAM applications , 1992, Proceedings Fourth International Conference on Software Engineering and Knowledge Engineering.

[34]  H. Penny Nii,et al.  Blackboard Systems, Part One: The Blackboard Model of Problem Solving and the Evolution of Blackboard Architectures , 1986, AI Mag..

[35]  L. Olsen,et al.  Chaos in biological systems. , 1985 .

[36]  Nicholas A. Peppas,et al.  Model predictive control for infusion pump insulin delivery , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[37]  H. P Nii,et al.  Blackboard Systems , 1986 .

[38]  C. Cobelli,et al.  A physiological simulation model of the glucose-insulin system , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[39]  W. J. Davis.  The distributed intelligent control of complex systems , 1999, Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296).