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Author Title [ Type(Asc)] Year
Thesis
Subramanian, S. Ganapathi. (2018). Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires. Electrical and Computer Engineering, University of Waterloo. Retrieved from http://hdl.handle.net/10012/13148
Journal Article
Subramanian, S. Ganapathi, Taylor, M. E. , Larson, K. , & Crowley, M. . (2022). Multi-Agent Advisor Q-Learning. Journal of Aritificial Intelligence Research (JAIR), 74, 1--74. Retrieved from https://jair.org/index.php/jair/article/view/13445/26794
Subramanian, S. Ganapathi, & Crowley, M. . (2018). Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models from Satellite Images. Journal of Frontiers in ICT- Environmental Informatics. Retrieved from https://www.frontiersin.org/articles/10.3389/fict.2018.00006/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_ICT&id=334036
Journal
Jain, P. , Coogan, S. C. P. , Subramanian, S. Ganapathi, Crowley, M. , Taylor, S. , & Flannigan, M. D. . (2020). A review of machine learning applications in wildfire science and management. Environmental Reviews. Retrieved from https://arxiv.org/pdf/2003.00646.pdf
Conference Paper
Subramanian, S. Ganapathi, Taylor, M. E. , Crowley, M. , & Poupart, P. . (2022). Decentralized Mean Field Games. In AAAI Conference on Artificial Intelligence (2022), Vancouver, BC, Canada. AAAI press. Retrieved from https://arxiv.org/pdf/2112.09099.pdf
Lee, K. Ming, Subramanian, S. Ganapathi, & Crowley, M. . (2021). Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments. In Neural Information Processing Systems (NeurIPS) - Deep Reinforcement Learning workshop. Retrieved from https://arxiv.org/pdf/2111.01100.pdf
Tkachuk, V. , Subramanian, S. Ganapathi, & Taylor, M. E. . (2021). The Effect of Q-function Reuse on the Total Regret of Tabular, Model-Free, Reinforcement Learning. In International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2021), London, UK - Adaptive Learning Agents Workshop. Retrieved from https://arxiv.org/pdf/2103.04416.pdf
Subramanian, S. Ganapathi, Taylor, M. E. , Crowley, M. , & Poupart, P. . (2021). Partially Observable Mean Field Reinforcement Learning. In International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2021), London, UK. Retrieved from https://arxiv.org/pdf/2012.15791.pdf
Gottipati, S. Krishna, Pathak, Y. , Nuttall, R. , Sahir, , Chunduru, R. , Touati, A. , Subramanian, S. Ganapathi, et al. (2020). Maximum Reward Formulation In Reinforcement Learning. In Deep Reinforcement Learning Workshop. NeurIPS 2020. Retrieved from https://arxiv.org/pdf/2010.03744.pdf
Bhalla, S. , Subramanian, S. Ganapathi, & Crowley, M. . (2020). Deep Multi Agent Reinforcement Learning for Autonomous Driving. In Canadian AI . Springer LNCS. Retrieved from https://link.springer.com/chapter/10.1007/978-3-030-47358-7_7
Subramanian, S. Ganapathi, Poupart, P. , Taylor, M. E. , & Hegde, N. . (2020). Multi Type Mean Field Reinforcement Learning. In International Conference on Autonomous Agents and Multi agent Systems (AAMAS 2020), Aukland, New Zealand. IFAAMAS. Retrieved from https://arxiv.org/pdf/2002.02513.pdf
Bhalla, S. , Subramanian, S. Ganapathi, & Crowley, M. . (2019). Learning Multi-Agent Communication with Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making. Retrieved from http://rldm.org/papers/abstracts.pdf
Subramanian, S. Ganapathi, Poupart, P. , Taylor, M. , & Hegde, N. . (2019). Multi Type Mean Field Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making. Retrieved from http://rldm.org/papers/abstracts.pdf
Bhalla, S. , Subramanian, S. Ganapathi, & Crowley, M. . (2019). Training Cooperative Agents for Multi-Agent Reinforcement Learning. In International Conference on Autonomous Agents and Multiagent System (AAMAS 2019), Montreal, Canada. Retrieved from http://www.ifaamas.org/Proceedings/aamas2019/pdfs/p1826.pdf
Subramanian, S. Ganapathi, & Crowley, M. . (2018). A Complementary Approach to Improve WildFire Prediction Systems. In Neural Information Processing Systems (AI for social good workshop). Retrieved from https://aiforsocialgood.github.io/2018/pdfs/track1/37_aisg_neurips2018.pdf
Subramanian, S. Ganapathi, Ghojogh, B. , Sambee, J. Singh, & Crowley, M. . (2018). Decision Assist For Self-Driving Cars. In 31st Canadian Conference on Artificial Intelligence, Toronto (pp. 381 - 387). Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-89656-4_44
Subramanian, S. Ganapathi, & Crowley, M. . (2018). Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Setting. In 31st Canadian Conference on Artificial Intelligence, Toronto (pp. 285-291). Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-89656-4_28
Subramanian, S. Ganapathi, & Crowley, M. . (2017). Learning Forest Wildfire Dynamics from Satellite Images using Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making (pp. 244-248). Retrieved from http://www.princeton.edu/~ndaw/RLDM17ExtendedAbstracts.pdf
Subramanian, S. Ganapathi, & P, A. Ganesh. (2015). Spatial Decision Support System for Industrial Robots. In Innovations in Marine Electrical and Electronics Engineering. Retrieved from https://uwaterloo.ca/scholar/sites/ca.scholar/files/s2ganapa/files/paper29.pdf