Read Entropy's recent Article "Distinguishing the Leading Agents in Classification Problems Using the Entropy-Based Metric"
Entropy MDPI
Entropy is an international and interdisciplinary peer-reviewed open access journal of entropy and information studies.
Authors: Evgeny Kagan and Irad Ben-Gal
Read full article at: https://www.mdpi.com/1099-4300/26/4/318
Abstract: The paper addresses the problem of distinguishing the leading agents in the group. The problem is considered in the framework of classification problems, where the agents in the group select the items with respect to certain properties. The suggested method of distinguishing the leading agents utilizes the connectivity between the agents and the Rokhlin distance between the subgroups of the agents. The method is illustrated by numerical examples. The method can be useful in considering the division of labor in swarm dynamics and in the analysis of the data fusion in the tasks based on the wisdom of the crowd techniques.
Keywords: leading agents; classification; entropy; Rokhlin metric
Associate Professor, Policy and Design Lab - Science, Technology and Society studies BIU
5 个月this mover from ReAct to graphs as a paradigm for agents is fascinating, I really want to test/play with this, just starting with Langraph but let me know if there is something easier/better for beginners - my main challenge is to have a way of engagement (of stakeholders) in the design of the agents