Publications

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[ Author(Asc)] Title Type Year
C
Crowley, M. & Poole, D., 2011. Policy gradient planning for environmental decision making with existing simulators. In 25th AAAI Conference on Artificial Intelligence (AAAI-11). San Francisco, pp. 1323–1330. Available at: https://www.scopus.com/record/display.uri?eid=2-s2.0-80055051332&origin=inward&txGid=de2006c39235aac9ba20cf0e76073dd9.
Crowley, M., 2011. Equilibrium Policy Gradients for Spatiotemporal Planning. University of British Columbia. Available at: http://hdl.handle.net/2429/38971.
Crowley, M., Nelson, J. & Poole, D., 2009. Seeing the Forest Despite the Trees : Large Scale Spatial-Temporal Decision Making. In Conference on Uncertainty in Artificial Intelligence (UAI09). Montreal, Canada, pp. 126–134. Available at: http://www.cs.ubc.ca/ crowley/papers/uai09-mark-crowley.pdf.
Crowley, M., Nelson, J. & Poole, D., 2009. Seeing the Forest Despite the Trees : Large Scale Spatial-Temporal Decision Making. In Conference on Uncertainty in Artificial Intelligence (UAI09). Montreal, Canada, pp. 126–134. Available at: http://www.cs.ubc.ca/ crowley/papers/uai09-mark-crowley.pdf.
Crowley, M. et al., 2007. Adding Local Constraints to Bayesian Networks. In Advances in Artificial Intelligence. Canadian AI Conference, Montreal, Quebec, Canada, 2007.: Springer Berlin Heidelberg, pp. 344–355. Available at: http://www.springerlink.com/content/u1j205nhr750m717/.
Crowley, M., 2005. Shielding Against Conditioning Side-Effects in Graphical Models. University of British Columbia.
Crowley, M., 2004. Evaluating Influence Diagrams. Unpublished Working Paper.
mltree.pdf papers2.pdf papers1.pdf Final Published Version
Carrillo, J. et al., 2019. Comparison of Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data. In The Transportation Association of Canada and Intelligent Transportation Systems Canada Joint Conference (TAC-ITS). Halifax, Canada, p. 16.
Carrillo, J. & Crowley, M., 2019. Integration of Roadside Camera Images and Weather Data for monitoring Winter Road Surface Conditions. In Canadian Association of Road Safety Professionals CARSP Conference. CARSP Conference, Calgary, Alberta. , p. 4 (Won best paper award!). Available at: http://www.carsp.ca/research/research-papers/research-papers-search/download-info/integration-of-roadside-camera-images-and-weather-data-for-monitoring-winter-road-surface-conditions/.
B
Bhalla, S., Subramanian, S.Ganapathi & Crowley, M., 2020. Deep Multi Agent Reinforcement Learning for Autonomous Driving. In Canadian Conference on Artificial Intelligence. Spring, Lecture Notes in Artificial Intelligence, p. 17.
deep_multi_agent_reinforcement_learning_for_autonomous_driving-full.pdf
Bhalla, S. et al., 2019. Compact Representation of a Multi-dimensional Combustion Manifold Using Deep Neural Networks. In European Conference on Machine Learning. Wurzburg, Germany, p. 8.
ecml_combustion_ml.pdf
Bhalla, S., Subramanian, S.G. & Crowley, M., 2019. Training Cooperative Agents for Multi-Agent Reinforcement Learning. In Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019). Montreal, Canada.
Bellinger, C. et al., 2021. Active Measure Reinforcement Learning for Observation Cost Minimization: A framework for minimizing measurement costs in reinforcement learning. In Canadian Conference on Artificial Intelligence. Springer, p. 12.
A
Allada, A.Krishna et al., 2021. Analysis of Language Embeddings for Classification of Unstructured Pathology Reports. In International Conference of the IEEE Engineering in Medicine and Biology Society. November. IEEE, p. 4.
Akgun, S.Alperen et al., 2021. Integrating Affective Expressions into the Search and Rescue Context in order to Improve Non-Verbal Human-Robot Interaction. In Workshop on Exploring Applications for Autonomous Non-Verbal Human-Robot Interactions (HRI). March. Virtual: ACM. Available at: https://sites.google.com/view/non-verbal-hri-2021/home.
Akgun, S.Alperen et al., 2020. Using Emotions to Complement Multi-Modal Human-Robot Interaction in Urban Search and Rescue Scenarios. In 22nd International Conference on Multimodal Interaction (ICMI-2020). October. Utrecht, the Netherlands, p. 9.

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