The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Help me make a dinner! Challenges when assisting humans in action planning
Abstract
A promising field of application for cognitive technical systems is individualised user assistance for complex tasks. Here, a companion system usually uses an AI planner to solve the underlying combinatorial problem. Often, the use of a bare black-box planning system is not sufficient to provide individualised assistance, but instead the user has to be able to control the process that generates the presented advice. Such an integration guarantees that the user will be satisfied with the assistance s/he is given, trust the advice more, and is thus more likely to follow it. In this paper, we provide a general theoretical view on this process, called mixed-initiative planning, and derive several research challenges from it.
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Results and recommendations for human-centered interaction with AI might differ depending on the context of use.
“Researchers have argued that results and recommendations for human-centered interaction with AI might differ depending on the context of use. For example, Behnke et al. (2017) and Leichtmann et al. (2018) argued that plan linearization of an AI-based planner could vary depending on the problem space.”
From Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task (2023) · cites this paper as Behnke et al., 2017
Citations
Cites
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“[38] B.”
BackgroundWhy and why not explanations improve the intelligibility of context-aware intelligent systems
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“A lack of understanding can be effectively mitigated by explaining the system’s behaviour to the user [39].”
Background
Flagged first, then by citations
Research works printed but not linked: 38
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Cited by
Sorted by citations
Leichtmann, B., Humer, C., Hinterreiter, A., Streit, M., & Mara, M. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107539 · Cited by 200
Self-citation
Metadata
- Authors
- Behnke, G., Leichtmann, B., Bercher, P., Holler, D., Nitsch, V., Baumann, M., & Biundo, S.
- Affiliations
- Universität Ulm (DE)
- Universität der Bundeswehr München (DE)
- Venue
- 2017 International Conference on Companion Technology (ICCT)
- Publisher
- IEEE
- Published
- 2017-09
- Pages
- 1-6
- OpenAlex
- W3046379547
- Cited by
- 7
- References
- 4
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 3 · 2019: 1 · 2018: 1
- FWCI
- 0.25
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ANU Open Research (Australian National University) (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Keywords
- mixed-initiative planning, companion systems, AI planners, trust in advice, task planning, research challenges
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