non-equilibrium-microwave-plasma-for-efficient-high-temperature

Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry

A flowing microwave plasma based methodology for converting electric energy into internal and/or translational modes of stable molecules with the purpose ...

Dutch Institute for Fundamental Energy Research

University of Trento

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.

Anthropic agency: a multiagent system for physiological processes.

Simulating and controlling physiological phenomena are notoriously complex tasks to tackle and require accurate models of the phenomena of interest. Currently, most physiological processes are described by a set of partial models capturing specific aspects of the phenomena, and usually their composition does not produce effective comprehensive models. A current open issue is thus the development of techniques able to effectively describe a phenomenon starting from partial models. This is particularly relevant for heart rate regulation modeling where a large number of heterogeneous partial models exists. In this paper we make the original proposal of adopting a multiagent paradigm, called anthropic agency, to provide a powerful and flexible tool for combining partial models of heart rate regulation for adaptive cardiac pacing applications. The partial models are embedded in autonomous computational entities, called agents, that cooperatively negotiate in order to smooth their conflicts on the values of the variables forming the global model the multiagent system provides. We experimentally evaluate our approach and we analyze its properties.

Article	Year
Anthropic agency: a multiagent system for physiological processes. Artificial intelligence in medicine\| PubMed ID: 12667741	2003
Combining rate-adaptive cardiac pacing algorithms via multiagent negotiation. IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society\| PubMed ID: 16445245	2006

Nicola Gatti

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