Multi-Agent Norm Perception and Induction in Distributed Healthcare
Journal:
arXiv
Published Date:
Dec 24, 2024
Abstract
This paper presents a Multi-Agent Norm Perception and Induction Learning
Model aimed at facilitating the integration of autonomous agent systems into
distributed healthcare environments through dynamic interaction processes. The
nature of the medical norm system and its sharing channels necessitates
distinct approaches for Multi-Agent Systems to learn two types of norms.
Building on this foundation, the model enables agents to simultaneously learn
descriptive norms, which capture collective tendencies, and prescriptive norms,
which dictate ideal behaviors. Through parameterized mixed probability density
models and practice-enhanced Markov games, the multi-agent system perceives
descriptive norms in dynamic interactions and captures emergent prescriptive
norms. We conducted experiments using a dataset from a neurological medical
center spanning from 2016 to 2020.
