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  4. Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research
 
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Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research

Journal
Hawaii International Conference on System Sciences (HICSS)
Type
conference paper
Date Issued
2023-01-06
Author(s)
Tolzin, Antonia
Janson, Andreas  
Research Team
IWI6
Abstract
Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future.
Funding(s)
International Postdoctoral Fellowship  
Language
English
Keywords
common ground
conversational agent
human-agent interaction
systematic review
HSG Classification
contribution to scientific community
Publisher place
Maui, Hawaii, USA
Event Title
Hawaii International Conference on System Sciences (HICSS)
Event Location
Maui, Hawaii, USA
Event Date
03-06 Jan 2023
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/107807
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

Eprints ID
267537
File(s)
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Thumbnail Image

open.access

Name

JML_890.pdf

Size

357.32 KB

Format

Adobe PDF

Checksum (MD5)

bb82344f7823997ee87b4b1ce182b255

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