Design and Evaluation of Explainable BDI Agents
Abstract
It is widely acknowledged that providing explanations is an important capability of intelligent systems. Explanation capabilities are useful, for example, in scenario-based training systems with intelligent virtual agents. Trainees learn more from scenario-based training when they understand why the virtual agents act the way they do. In this paper, we present a model for explainable BDI agents which enables the explanation of BDI agent behavior in terms of underlying beliefs and goals. Different explanation algorithms can be specified in the model, generating different types of explanations. In a user study (n=20), we compare four explanation algorithms by asking trainees which explanations they consider most useful. Based on the results, we discuss which explanation types should be given under what conditions.
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Some contributions include the ability of a model to be interactive with the user as one of the goals targeted by an explainable ML model.
“some contributions [50, 59] include the ability of a model to be interactive with the user as one of the goals targeted by an explainable ML model.”
From Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI (2020) · cites this paper as [50]
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- Authors
- Harbers, M., van den Bosch, K., & Meyer, J.-J.
- Affiliations
- Netherlands Organisation for Applied Scientific Research (NL)
- Utrecht University (NL)
- ORCID
- Harbers, Maaike
- Venue
- 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
- Publisher
- IEEE
- Published
- 2010-08
- Pages
- 125-132
- OpenAlex
- W1972577679
- Cited by
- 70
- References
- 24
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 2 · 2023: 7 · 2022: 15 · 2021: 9 · 2020: 10 · 2019: 4 · 2018: 4 · 2017: 4 · 2015: 1 · 2012: 2
- FWCI
- 1.29
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (publishedVersion)
- TNO Repository (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- BDI agents, belief-desire explanation, scenario-based training, intelligent virtual agents, user study
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