Fostering Cooperation in Structured Populations Through Local and Global Interference Strategies
- Submitting institution
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Teesside University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 24740919
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)
- First page
- 289
- Volume
- -
- Issue
- -
- ISSN
- 2162-1160
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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- Request cross-referral to
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- 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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3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper was presented at IJCAI and the work has been further developed as follows: (1) providing a basis for PhD study which produced its first output in 2019 (10.1162/isal_a_00181), with a second paper under review; (2) one co-author developed the work to examine how to optimally incentivise populations of self-interested agents (resulting in additional publications in the submission’s output pool); (3) the study provides foundational work underpinning two successful grants: "Incentives for Safety Agreement Compliance in AI Race" (Future of Life Institute, 2018 - 2020) and “Incentives for Commitment Compliance” (Leverhulme Research Fellowship, 2020-2022).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -