Demonstrating social error recovery with AgentFactory

Robert Ross, Rem Collier, G. M.P. O'Hare

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In real world applications, agents - be they software agents or autonomous robots - inevitably face erroneous situations that have not been planned for. Re-planning can sometimes provide solutions to problems, but it is computationally expensive and rarely practical. We argue that replanning is not necessarily the last resort. Instead, during erroneous circumstances, agents should always take advantage of other agents in their environment. In this paper we report on early work that looks at Social Error Recovery as a particular class of exception handling that allows agents to resolve erroneous situations that are beyond their direct control. We also show how the AgentFactory Framework and its language AF-APL have been directly extended to support a basic model of Social Error Recovery.

Original languageEnglish
Title of host publicationProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
EditorsN.R. Jennings, C. Sierra, L. Sonenberg, M. Tambe
Pages1424-1425
Number of pages2
Publication statusPublished - 2004
Externally publishedYes
EventProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004 - New York, NY, United States
Duration: 19 Jul 200423 Jul 2004

Publication series

NameProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
Volume3

Conference

ConferenceProceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004
Country/TerritoryUnited States
CityNew York, NY
Period19/07/0423/07/04

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