The Positive Effect of User Faults over Agent Perception in Collaborative Settings and Its Use in Agent Design

Reut Asraf, Chen Rozenshtein, David Sarne

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

Abstract

This paper studies the effect of user’s own task-related faults over her satisfaction with a fault-prone agent in a human-agent collaborative setting. Through a series of extensive experiments we find that user faults make the user more tolerant to agent faults, and consequently more satisfied with the collaboration, in particular compared to the case where the user is performing faultlessly. This finding can be utilized for improving the design of collaborative agents. In particular, we present a proof-of-concept for such augmented design, where the agent, whenever in charge of allocating the tasks or can pick its own tasks, deliberately leave the user with a relatively difficult task for increasing the chance for a user fault, which in turn increases user satisfaction.

Original languageEnglish
Title of host publicationDistributed Artificial Intelligence - 3rd International Conference, DAI 2021, Proceedings
EditorsJie Chen, Jérôme Lang, Christopher Amato, Dengji Zhao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages129-149
Number of pages21
ISBN (Print)9783030946616
DOIs
StatePublished - 2022
Event3rd International Conference on Distributed Artificial Intelligence, DAI 2021 - Shanghai, China
Duration: 17 Dec 202118 Dec 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13170 LNAI

Conference

Conference3rd International Conference on Distributed Artificial Intelligence, DAI 2021
Country/TerritoryChina
CityShanghai
Period17/12/2118/12/21

Keywords

  • Human-agent collaboration
  • Human-agent interaction
  • Intelligent user interfaces

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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