Hospitals have a specified set of antibiotics for restricted use (ARU), very expensive, which are only recommended for special pathologies. The pharmacy department daily checks the prescription of this kind of antibiotics since it is often the case that, after a careful analysis, one can get the same therapeutic effects by using normal antibiotics which are much cheaper and usually less aggressive. In this paper, we describe a multi-agent system to help in the revision of medical prescriptions containing antibiotics of restricted use. The proposed approach attaches an agent to each patient which is responsible of checking different medical aspects related to his/her prescribed therapy. A pharmacy agent is responsible for analyzing it and suggesting alternative antibiotic treatments. All these agents are integrated in a hospital distributed scenario composed by many different kinds of software and human agents. This patient-centered multi-agent scenario is specified using the design methodology of Electronic Institutions.
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http://dx.doi.org/10.1016/s0933-3657(03)00006-x | DOI Listing |
Sci Rep
January 2025
Zhejiang Gongshang University Hangzhou College of Commerce, Hangzhou, Zhejiang, China.
Service transformation plays a pivotal role in achieving the sustainable development of the sports industry. This study originates from the interactive relationships among sports enterprises, consumers, and regulatory authorities, proposing a logical framework for the service transformation of the sports industry. Furthermore, a three-party evolutionary game model is constructed to explore the strategic evolution and stability conditions under both single-agent and multi-agent scenarios.
View Article and Find Full Text PDFISA Trans
January 2025
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran. Electronic address:
This paper introduces a fully distributed model-free adaptive control (MFAC) approach for consensus tracking in multi-agent systems (MASs) with compact form data linearization (CFDL). Unlike prior methods that require agents to know the full communication graph, our approach allows each agent to configure its controller using only local information from its neighbors, achieving a fully distributed control. Therefore, our method easily supports scenarios where agents dynamically join or leave MAS.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Computer Science, Peking University, Beijing 100871, China.
Multi-agent systems often face challenges such as elevated communication demands, intricate interactions, and difficulties in transferability. To address the issues of complex information interaction and model scalability, we propose an innovative hierarchical graph attention actor-critic reinforcement learning method. This method naturally models the interactions within a multi-agent system as a graph, employing hierarchical graph attention to capture the complex cooperative and competitive relationships among agents, thereby enhancing their adaptability to dynamic environments.
View Article and Find Full Text PDFISA Trans
January 2025
College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, Hunan, China. Electronic address:
Approximation-free control effectively addresses uncertainty and disturbances without relying on approximation techniques such as fuzzy logic systems (FLS) and neural networks (NNs). However, singularity problems-where signals exceed preset boundaries under dynamic operating conditions-remain a challenge. This paper proposes an improved approximation-free control (I-AFC) method for the multi-agent system, which introduces a novel singularity compensator, providing a low-complexity design with exceptional adaptability while reducing the risk of singularity issues under changing working conditions (random initial values, system parameter variations, and changes in topology graph and followers' dynamics).
View Article and Find Full Text PDFJ Biomed Inform
January 2025
ITMO University, Saint Petersburg, Russia. Electronic address:
The optimization in the ambulance dispatching process is significant for patients who need early treatments. However, the problem of dynamic ambulance redeployment for destination hospital selection has rarely been investigated. The paper proposes an approach to model and simulate the ambulance dispatching process in multi-agent healthcare environments of large cities.
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