Aya Saad, Anne HÃ¥kansson. RAMARL: Robustness Analysis with Multi-Agent Reinforcement Learning - Robust Reasoning in Autonomous Cyber-Physical Systems. In Matteo Cristani, Carlos Toro 0001, Cecilia Zanni-Merk, Robert J. Howlett, Lakhmi C. Jain, editors, Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, Verona, Italy and Virtual Event, 7-9 September 2022. Volume 207 of Procedia Computer Science, pages 3662-3671, Elsevier, 2022. [doi]
@inproceedings{SaadH22, title = {RAMARL: Robustness Analysis with Multi-Agent Reinforcement Learning - Robust Reasoning in Autonomous Cyber-Physical Systems}, author = {Aya Saad and Anne HÃ¥kansson}, year = {2022}, doi = {10.1016/j.procs.2022.09.426}, url = {https://doi.org/10.1016/j.procs.2022.09.426}, researchr = {https://researchr.org/publication/SaadH22}, cites = {0}, citedby = {0}, pages = {3662-3671}, booktitle = {Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, Verona, Italy and Virtual Event, 7-9 September 2022}, editor = {Matteo Cristani and Carlos Toro 0001 and Cecilia Zanni-Merk and Robert J. Howlett and Lakhmi C. Jain}, volume = {207}, series = {Procedia Computer Science}, publisher = {Elsevier}, }