Resource-bounded Norm Monitoring in Multi-agent Systems
- Submitting institution
-
King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 111090789
- Type
- D - Journal article
- DOI
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10.1613/jair.1.11206
- Title of journal
- Journal Artificial Intelligence Research
- Article number
- -
- First page
- 153
- Volume
- 62
- Issue
- -
- ISSN
- 1076-9757
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- 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
-
0
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Resource-bounded multi-agent systems are a well-known problem in AI. The literature addressing their verification demonstrates the limitations on what can be verified at design-time, but few works are concerned with run-time monitoring. This work proposes the first resource-bounded norm monitor, and an optimization method to select monitoring resources. The paper includes formal proofs of the monitor’s soundness and correctness, and experimental data demonstrating the practicality and effectiveness of the optimization method in both synthetic and benchmark scenarios. This article expands previous work presented at IJCAI’16 (https://www.ijcai.org/Proceedings/16/Papers/037.pdf) and is being applied to monitor user-defined norms in personal assistants (EPSRC SAIS project).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -