A unified framework for multi-agent agreement

Kiran Lakkaraju, Les Gasser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-Agent Agreement Problems (MAP) - the ability of a population of agents to search out and converge on a common state - are central issues in many multi-agent settings, from distributed sensor networks, to meeting scheduling, to development of norms, conventions, and language. While much work has been done on particular agreement problems no unifying framework exists for comparing MAPs that vary in, e.g., strategy space complexity, inter-agent accessibility, and solution type, and understanding their relative complexities. We present such a unification, the Distributed Optimal Agreement (DOA) framework, and show how it captures a wide variety of agreement problems. To demonstrate DOA and its power we apply it to convention evolution.

Original languageEnglish (US)
Title of host publicationAAMAS'07 - Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems
Pages88-90
Number of pages3
DOIs
StatePublished - 2007
Externally publishedYes
Event6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07 - Honolulu, HI, United States
Duration: May 14 2008May 18 2008

Publication series

NameProceedings of the International Conference on Autonomous Agents

Other

Other6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07
Country/TerritoryUnited States
CityHonolulu, HI
Period5/14/085/18/08

Keywords

  • Language evolution
  • Multi agent agreement problems
  • Multi agent systems

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications
  • Theoretical Computer Science

Fingerprint

Dive into the research topics of 'A unified framework for multi-agent agreement'. Together they form a unique fingerprint.

Cite this