A Memetic Multi-Agent Demonstration Learning Approach with Behavior Prediction
- Submitting institution
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Teesside University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 7959336
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems
- First page
- 539
- Volume
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- Issue
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- ISSN
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- Open access status
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- Month of publication
- May
- Year of publication
- 2016
- URL
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- 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
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- 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
- This work complements meme-based systems with agent behaviour prediction methods. It resulted from a collaboration with A/P Yaqing Hou in Dalian University of Technology, China, and was further supported by a research grant from the National Natural Science Foundation of China (61906032; RMB 240,000; Multiagent Transfer Reinforcement Learning upon the Sub-Modular Function Optimization). The research also underpins collaboration with Modus Seabed Intervention Ltd. in an Innovate UK KTP (11646).
- Author contribution statement
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- Non-English
- No
- English abstract
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