Modeling the Cooperative Process of Learning a Task

TL;DR

This paper introduces a mathematical model for cooperative learning in a group, analyzing how expertise develops through interactions and network structure, with implications for understanding collective skill acquisition.

Contribution

It presents a novel mathematical framework for modeling the dynamics of cooperative learning and expertise development within a Transactive Memory System.

Findings

Non-stubborn agents asymptotically reach the most expert level

Stubborn agents' influence depends on network connectivity

The model highlights the importance of interaction structure in learning

Abstract

In this paper, we propose a mathematical model for a Transactive Memory System (TMS) involved in the cooperative process of learning a task. The model is based on an intertwined dynamics involving both the individuals level of expertise and the interaction network among the cooperators. The model shows that if all the agents are non-stubborn, then all of them are able to acquire the competence of the most expert members of the group, asymptotically reaching their level of proficiency. Conversely, when dealing with all stubborn agents, the capability to pass on the task depends on the connectedness properties of the interaction graph.