---
title: "Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems"
authors:
  - "Nancy Fulda"
  - "Dan Ventura"
doi: ""
url: "https://ijcai.org/proceedings/2007/125"
pdf: "https://ijcai.org/proceedings/2007/0125.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "780-784"
track: ""
keywords:
---

# Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems

Nancy Fulda, Dan Ventura

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 780-784.

## Abstract

We present a conceptual framework for creating Q-learning-based algorithms that converge to optimal equilibria in cooperative multiagent settings. This framework includes a set of conditions that are sufficient to guarantee optimal system performance. We demonstrate the efficacy of the framework by using it to analyze several well-known multi-agent learning algorithms and conclude by employing it as a design tool to construct a simple, novel multiagent learning algorithm.