Skip to main content

Research Repository

Advanced Search

Agile Planning for Real-World Disaster Response

Wu, Feng; Ramchurn, Sarvapali D.; Jiang, Wenchao; Fischer, Joel E.; Rodden, Tom; Jennings, Nicholas R.

Authors

Feng Wu

Sarvapali D. Ramchurn

Wenchao Jiang

TOM RODDEN TOM.RODDEN@NOTTINGHAM.AC.UK
Professor of Computer Science

Nicholas R. Jennings



Abstract

We consider a setting where an agent-based planner instructs teams of human emergency responders to perform tasks in the real world. Due to uncertainty in the environment and the inability of the planner to consider all human preferences and all attributes of the real-world, humans may reject plans computed by the agent. A na¨ıve solution that replans given a rejection is inefficient and does not guarantee the new plan will be acceptable. Hence, we propose a new model re-planning problem using a Multi-agent Markov Decision Process that integrates potential rejections as part of the planning process and propose a novel algorithm to efficiently solve this new model. We empirically evaluate our algorithm and show that it outperforms current benchmarks. Our algorithm is also shown to perform better in pilot studies with real humans.

Citation

Wu, F., Ramchurn, S. D., Jiang, W., Fischer, J. E., Rodden, T., & Jennings, N. R. (2015). Agile Planning for Real-World Disaster Response. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. , (132-138)

Conference Name International Joint Conference on Artificial Intelligence (IJCAI-15)
Conference Location Buenos Aires, Argentina
Start Date Jul 25, 2015
End Date Jul 31, 2015
Online Publication Date Jul 25, 2015
Publication Date Jul 25, 2015
Deposit Date Jan 29, 2016
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Volume 2015-July
Pages 132-138
Book Title Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence
ISBN 9781577357384
Public URL http://eprints.nottingham.ac.uk/id/eprint/31398
Publisher URL https://dl.acm.org/doi/10.5555/2832249.2832268
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
Additional Information Published in: Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence: Buenos Aires, Argentina, 25–31 July 2015. Palo Alto, Calif. : AAAI Press/International Joint Conferences on Artificial Intelligence, 2015. ISBN: 978-1-5773-5738-4, pp. 132-138