Distributed Artificial Intelligence

The Distributed Artificial Intelligence group explores social and technological contexts of interacting intelligent entities, including multi-agent systems, agent-based simulation, crowd computing, semantic web, provenance, norms, incentives, knowledge graphs, trust and reputation.

The group marries artificial intelligence expertise with social, political and economic theories and data to pursue research that has strong technological and societal relevance and benefit. We take inspiration from tools and techniques in human societies for the engineering of effective decentralised technology and responsible AI, and develop computational models for analysing social, political and economic phenomena to improve the effectiveness and fairness of policy and practice and to build socio-technical systems that combine machine algorithms with human and social capabilities.

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Horizon 2020 programme that helps 15 citizen science communities around Europe fight pollution

A Decade of Knowledge Graphs in Natural Language Processing: A Survey
Simperl, E., 27 Sep 2022, (Accepted/In press) 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing. 14 p. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
A Methodology for DSML-assisted Participatory Agent-Based Enterprise Modelling
Godfrey, T., Batra, R., Douthwaite, S., Edgeworth, J., Miles, S. & Zschaler, S., 14 Sep 2022, (Accepted/In press) Practice of Enterprise Modelling 2022. Springer Nature Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Accounting for Strategic Response in Limit Order Book Dynamics
Ji, Q. & Ventre, C., 14 Sep 2022, (Accepted/In press) Proceedings of the 24th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2022). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Denoised Labels for Financial Time Series Data via Self-Supervised Learning
Ma, M., Ventre, C. & Polukarov, M., 1 Sep 2022, (Accepted/In press) Proceedings of the 3rd ACM International Conference on AI in Finance: ICAIF'22. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Incentivising Market Making in Financial Markets
Ji, Q. & Ventre, C., 1 Sep 2022, (Accepted/In press) Proceedings of the 3rd ACM International Conference on AI in Finance: ICAIF'22. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Model-Agnostic Pricing of Exotic Derivatives Using Signatures
Alden, A., Ventre, C., Horvath, B. & Lee, G., 1 Sep 2022, (Accepted/In press) Proceedings of the 3rd ACM International Conference on AI in Finance: ICAIF'22. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Synthetic Data Augmentation for Deep Reinforcement Learning in Financial Trading
Liu, C., Ventre, C. & Polukarov, M., 1 Sep 2022, (Accepted/In press) Proceedings of the 3rd ACM International Conference on AI in Finance: ICAIF'22. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
From Subsymbolic to Symbolic: A Blueprint for Investigation
Pober, J., Luck, M. & Rodrigues, O., 29 Jul 2022, (Accepted/In press) CEUR Workshop Proceedings: NESY 2022: 16th International Workshop on Neural-Symbolic Learning and Reasoning. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Financial Networks with Singleton Liability Priorities
Ioannidis, S., De Keijzer, B. & Ventre, C., 1 Jul 2022, (Accepted/In press) Proceedings of the 15th International Symposium on Algorithmic Game Theory (SAGT). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Strong Approximations and Irrationality in Financial Networks with Derivatives
Ioannidis, S., De Keijzer, B. & Ventre, C., 28 Jun 2022, Proceedings of the 49th EATCS International Colloquium on Automata, Languages, and Programming (ICALP): Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik. Vol. 229. (LIPIcs). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review. DOIs: https://doi.org/, https://drops.dagstuhl.de/opus/volltexte/2022/16417/

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Group lead

Maria Polukarov

Senior Lecturer in Computer Science

Distributed Artificial Intelligence

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Group lead

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