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Why Bad Coffee? Explaining BDI Agent Behaviour with Valuings (Extended Abstract)
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- Winikoff, Michael (author)
- Victoria University Of Wellington, Wellington, New Zealand
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- Sidorenko, Galina, 1985- (author)
- Högskolan i Halmstad,Akademin för informationsteknologi,Halmstad University, Sweden
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- Dignum, Virginia, Professor (author)
- Umeå universitet,Institutionen för datavetenskap,Umeå University, Umea, Sweden
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- Palo Alto, CA : AAAI Press, 2022
- 2022
- English.
- In: IJCAI International Joint Conference on Artificial Intelligence. - Palo Alto, CA : AAAI Press. - 9781956792003 ; , s. 5782-5786
- Conference paper (peer-reviewed)
Abstract
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- An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results. © 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.
Subject headings
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv -- Företagsekonomi (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business -- Business Administration (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
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- ref (subject category)
- kon (subject category)
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