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Explainable Agents and Robots: Results from a Systematic Literature Review
Umeå University, Faculty of Science and Technology, Department of Computing Science. (XAI)
Umeå University, Faculty of Science and Technology, Department of Computing Science. (XAI)
(HES-SO)
Umeå University, Faculty of Science and Technology, Department of Computing Science. (XAI)ORCID iD: 0000-0002-8078-5172
2019 (English)In: Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 13–17, 2019, IFAAMAS / [ed] N. Agmon, M. E. Taylor, E. Elkind, M. Veloso, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Humans are increasingly relying on complex systems that heavily adopts Artificial Intelligence (AI) techniques. Such systems are employed in a growing number of domains, and making them explainable is an impelling priority. Recently, the domain of eXplainable Artificial Intelligence (XAI) emerged with the aims of fostering transparency and trustworthiness. Several reviews have been conducted. Nevertheless, most of them deal with data-driven XAI to overcome the opaqueness of black-box algorithms. Contributions addressing goal-driven XAI (e.g., explainable agency for robots and agents) are still missing. This paper aims at filling this gap, proposing a Systematic Literature Review. The main findings are (i) a considerable portion of the papers propose conceptual studies, or lack evaluations or tackle relatively simple scenarios; (ii) almost all of the studied papers deal with robots/agents explaining their behaviors to the human users, and very few works addressed inter-robot (inter-agent) explainability. Finally, (iii) while providing explanations to non-expert users has been outlined as a necessity, only a few works addressed the issues of personalization and context-awareness

Place, publisher, year, edition, pages
2019.
Keywords [en]
Explainable AI, goal-based XAI, autonomous agents, human-robot interaction
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:umu:diva-158024OAI: oai:DiVA.org:umu-158024DiVA, id: diva2:1303810
Conference
AAMAS 2019
Available from: 2019-04-10 Created: 2019-04-10 Last updated: 2019-04-23

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http://humanrobotinteraction.org/2019/

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Anjomshoae, SuleNajjar, AmroFrämling, Kary

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CiteExportLink to record
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Citation style
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