A multi-agent model of hierarchical decision dynamics

TL;DR

This paper introduces a hierarchical multi-agent decision model that separates observation, judgment, and action, demonstrating how agents coordinate through shared judgments to improve decision outcomes in uncertain environments.

Contribution

It presents a novel hierarchical binary-tree model of multi-agent decision dynamics with explicit separation of decision steps and a mechanism for coordination via shared judgments.

Findings

Agents coordinate effectively through shared judgments.

Hierarchical structure improves decision consistency.

Model captures complex decision dynamics in uncertain settings.

Abstract

Decision making can be difficult when there are many actors (or agents) who may be coordinating or competing to achieve their various ideas of the optimum outcome. Here I present a simple decision making model with an explicitly hierarchical binary-tree structure, and evaluate how this might cooperate to take actions that match its various evaluations of the uncertain state of the world. Key features of agent behaviour are (a) the separation of its decision making process into three distinct steps: observation, judgement, and action; and (b) the evolution of coordination by the sharing of judgements.