# Dynamic Models of Appraisal Networks Explaining Collective Learning

arXiv: https://arxiv.org/abs/1609.09546 · HTML: https://mlsanity.com/paper/1609.09546/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2016.

## Built on by (most cited first, 1 of 1)

- [Modeling Human-AI Team Decision Making](https://mlsanity.com/paper/2201.02759/) (2022)

## Abstract (arXiv)

This paper proposes models of learning process in teams of individuals who collectively execute a sequence of tasks and whose actions are determined by individual skill levels and networks of interpersonal appraisals and influence. The closely-related proposed models have increasing complexity, starting with a centralized manager-based assignment and learning model, and finishing with a social model of interpersonal appraisal, assignments, learning, and influences. We show how rational optimal behavior arises along the task sequence for each model, and discuss conditions of suboptimality. Our models are grounded in replicator dynamics from evolutionary games, influence networks from mathematical sociology, and transactive memory systems from organization science.