---
title: "Fast convergence to satisfying distributions"
authors:
  - "Teddy Candale"
  - "Sandip Sen"
doi: ""
url: "https://ijcai.org/proceedings/2005/338"
pdf: "https://ijcai.org/proceedings/2005/0338.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "1657-1657"
track: ""
keywords:
---

# Fast convergence to satisfying distributions

Teddy Candale, Sandip Sen

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 1657-1657.

## Abstract

We investigate an environment where selfinterested agents have to find high-quality service resources. Agents have common knowledge about resources which are able to provide these services. The performance of resources is measured by the satisfaction obtained by agents using them. The performance of a resource depends on its intrinsic capability and its current load. We use a satisfying rather than an optimizing framework, where agents are content to receive service quality above a threshold. We introduce a formal framework to characterize the convergence of agents to a state where each agent is satisfied with the performance of the service it is currently using. We analyzed the convergence behavior of such a system and identified a mechanism to speed up convergence.