Approximating behavioral equivalence for scaling solutions of I-DIDs
- Submitting institution
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Teesside University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 6459934
- Type
- D - Journal article
- DOI
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10.1007/s10115-015-0912-x
- Title of journal
- Knowledge and Information Systems
- Article number
- -
- First page
- 511
- Volume
- 49
- Issue
- 2
- ISSN
- 0219-1377
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is a full profile of solutions to interactive dynamic influence diagrams (I-DIDs) – a well-recognized decision framework for multiple agents. It provides scalable algorithms for I-DIDs, which leads to successful applications in real-world scenarios. The algorithms have been adopted by Shanghai SinceMe Networking & Technology LTD (http://www.sinceme.com/about?lang=en; statement available on request) for improving AI engines in commercial games with significant savings in game development.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -