Publications
. (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
. (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
. (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
. (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
. (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
(2020). Maximum Reward Formulation In Reinforcement Learning. In Deep Reinforcement Learning Workshop. NeurIPS 2020. Retrieved from https://arxiv.org/pdf/2010.03744.pdf
. (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
. (2020). A review of machine learning applications in wildfire science and management. Environmental Reviews. Retrieved from https://arxiv.org/pdf/2003.00646.pdf
. (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
. (2019). Learning Multi-Agent Communication with Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making. Retrieved from http://rldm.org/papers/abstracts.pdf
. (2019). Multi Type Mean Field Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making. Retrieved from http://rldm.org/papers/abstracts.pdf
. (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
. (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
. (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
. (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
. (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
. (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
. (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
(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
