Decision-Theoretic Planning Under Anonymity in Agent Populations
- Submitting institution
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Teesside University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 6459853
- Type
- D - Journal article
- DOI
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10.1613/jair.5449
- Title of journal
- Journal of Artificial Intelligence Research
- Article number
- -
- First page
- 725
- Volume
- 59
- Issue
- -
- ISSN
- 1076-9757
- Open access status
- Deposit exception
- Month of publication
- -
- Year of publication
- 2017
- 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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2
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The core technology developed in this paper is supporting ongoing work with Visualsoft to model the collective behaviour of high volume e-commence platform customers (https://www.weareumi.co.uk/news/sectors/finance/visualsoft-set-to-gain-valuable-insights-into-ecommerce-market-with-help-from-teesside-university). This development is funded by an Innovate UK Knowledge Transfer Partnership (011568).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -