article

Logics of common ground

Authors:

Yoshihisa KashimaAuthors Info & Claims

Journal of Artificial Intelligence Research, Volume 58, Issue 1

Pages 859 - 904

Published: 01 January 2017 Publication History

Abstract

According to Clark's seminal work on common ground and grounding, participants collaborating in a joint activity rely on their shared information, known as common ground, to perform that activity successfully, and continually align and augment this information during their collaboration. Similarly, teams of human and artificial agents require common ground to successfully participate in joint activities. Indeed, without appropriate information being shared, using agent autonomy to reduce the workload on humans may actually increase workload as the humans seek to understand why the agents are behaving as they are. While many researchers have identified the importance of common ground in artificial intelligence, there is no precise definition of common ground on which to build the foundational aspects of multi-agent collaboration. In this paper, building on previously-defined modal logics of belief, we present logic definitions for four different types of common ground. We define modal logics for three existing notions of common ground and introduce a new notion of common ground, called salient common ground. Salient common ground captures the common ground of a group participating in an activity and is based on the common ground that arises from that activity as well as on the common ground they shared prior to the activity. We show that the four definitions share some properties, and our analysis suggests possible refinements of the existing informal and semi-formal definitions.

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Cited By

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Caldwell SSweetser PO’Donnell NKnight MAitchison MGedeon TJohnson DBrereton MGallagher MConroy D(2022)An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and TransferabilityACM Transactions on Interactive Intelligent Systems10.1145/351425712:3(1-36)Online publication date: 26-Jul-2022
https://dl.acm.org/doi/10.1145/3514257
Alshehri AMiller TSonenberg L(2021)Modeling communication of collaborative multiagent system under epistemic planningInternational Journal of Intelligent Systems10.1002/int.2253636:10(5959-5980)Online publication date: 26-Aug-2021
https://dl.acm.org/doi/10.1002/int.22536
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Logics of common ground
1. Theory of computation
  1. Logic

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cover image Journal of Artificial Intelligence Research

Journal of Artificial Intelligence Research Volume 58, Issue 1

January 2017

956 pages

ISSN:1076-9757

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AI Access Foundation

El Segundo, CA, United States

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Published: 01 January 2017

Published in JAIR Volume 58, Issue 1

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Cited By

Ligthart MNeerincx MHindriks K(2023)It Takes Two: Using Co-creation to Facilitate Child-Robot Co-regulationACM Transactions on Human-Robot Interaction10.1145/359381212:4(1-32)Online publication date: 23-Jun-2023
https://dl.acm.org/doi/10.1145/3593812
Caldwell SSweetser PO’Donnell NKnight MAitchison MGedeon TJohnson DBrereton MGallagher MConroy D(2022)An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and TransferabilityACM Transactions on Interactive Intelligent Systems10.1145/351425712:3(1-36)Online publication date: 26-Jul-2022
https://dl.acm.org/doi/10.1145/3514257
Alshehri AMiller TSonenberg L(2021)Modeling communication of collaborative multiagent system under epistemic planningInternational Journal of Intelligent Systems10.1002/int.2253636:10(5959-5980)Online publication date: 26-Aug-2021
https://dl.acm.org/doi/10.1002/int.22536
Blache PChaminade TNgyuen NOchs MLefèvre F(2017)Dialogue management in task-oriented dialogue systemsProceedings of the 1st ACM SIGCHI International Workshop on Investigating Social Interactions with Artificial Agents10.1145/3139491.3139507(4-8)Online publication date: 13-Nov-2017
https://dl.acm.org/doi/10.1145/3139491.3139507

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