Thesis
Reliable Decision-Making with Imprecise Models (Doctoral Dissertation)
Sandhya Saisubramanian, University of Massachusetts Amherst.
Refereed Conferences/ Journals/ Technical Magazine Articles
Minimizing Negative Side Effects in Cooperative Multi-Agent Systems using Distributed Coordination
Moumita Choudhury, Sandhya Saisubramanian, Hao Zhang, and Shlomo Zilberstein. In Proceedings of the 37th International FLAIRS Conference, 2024.
*Also appeared as an extended abstract in proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024.
User-Aligned Assessment of Agent Learning and Operation for Reliable Autonomy
Sandhya Saisubramanian. AAAI Spring Symposium on User-Aligned Assessment of Adaptive AI Systems, 2024.
Explanation-Guided Reward Alignment
Saaduddin Mahmud, Sandhya Saisubramanian, and Shlomo Zilberstein. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
Planning and Learning for Non-Markovian Negative Side Effects using Finite State Controllers
Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, and Shlomo Zilberstein. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
Avoiding Negative Side Effects of Autonomous Systems in the Open World
Sandhya Saisubramanian, Ece Kamar, and Shlomo Zilberstein. In the Journal of Artificial Intelligence Research (JAIR), 2022.
Metareasoning for Safe Decision Making in Autonomous Systems
Justin Svegliato, Connor Basich, Sandhya Saisubramanian, and Shlomo Zilberstein. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2022.
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems
Sandhya Saisubramanian, Shlomo Zilberstein, and Ece Kamar. AI Magazine Winter 2022 edition.
Learning to Generate Fair Clusters from Demonstrations
Sainyam Galhotra, Sandhya Saisubramanian, and Shlomo Zilberstein. In Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2021.
Understanding User Attitudes Towards Negative Side Effects of AI Systems
Sandhya Saisubramanian, Shannon C. Roberts, and Shlomo Zilberstein. In Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Late-Breaking Work Track, 2021.
Mitigating Negative Side Effects via Environment Shaping (Extended Abstract)
Sandhya Saisubramanian and Shlomo Zilberstein. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021. [full paper]
A Multi-Objective Approach to Mitigate Negative Side Effects
Sandhya Saisubramanian, Ece Kamar, and Shlomo Zilberstein. In Proceedings of 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020. Distinguished paper award.
Balancing the Tradeoff Between Clustering Value and Interpretability
Sandhya Saisubramanian*, Sainyam Galhotra*, and Shlomo Zilberstein. In Proceedings of AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2020. (* equal contribution).
Satisfying Social Preferences in Ridesharing Services
Sandhya Saisubramanian, Connor Basich, Shlomo Zilberstein, and Claudia Goldman. In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
Adaptive Outcome Selection for Planning With Reduced Models
Sandhya Saisubramanian and Shlomo Zilberstein. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
Planning in Stochastic Environments with Goal Uncertainty
Sandhya Saisubramanian, Kyle Hollins Wray, Luis Pineda, and Shlomo Zilberstein. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
Planning Using a Portfolio of Reduced Models (Extended Abstract)
Sandhya Saisubramanian, Shlomo Zilberstein, and Prashant Shenoy. In Proceedings of 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
Risk Based Optimization for Emergency Medical Systems
Sandhya Saisubramanian, Pradeep Varakantham, and Hoong Chuin Lau. In Proceedings of 29th AAAI Conference on Artificial Intelligence (AAAI), 2015.
STREETS: Game-Theoretic Traffic Patrolling with Exploration and Exploitation
Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, and Milind Tambe. In Proceedings of Innovative Applications in Artificial Intelligence (IAAI) at 28th AAAI Conference on Artificial Intelligence, 2014.
Refereed Workshop Publications
REVEALE: Reward Verification and Learning Using Explanations
Saaduddin Mahmud, Sandhya Saisubramanian, and Shlomo Zilberstein. AAAI Workshop on Artificial Intelligence Safety, 20123.
Using Metareasoning to Maintain and Restore Safety for Reliably Autonomy
Justin Svegliato, Connor Basich, Sandhya Saisubramanian and Shlomo Zilberstein. IJCAI Workshop on Robust and Reliable Autonomy in the Wild (R2AW), 2021.
Identifying Missing Features in State Representation for Safe Decision-Making
Minori Narita, Sandhya Saisubramanian, Roderic A. Grupen and Shlomo Zilberstein. ICML Workshop on Human-AI Collaboration in Sequential Decision-Making, 2021.
Efficient Integration of Complementary Solvers for Quantum Circuit Compilation
Sandhya Saisubramanian, Minh Do, Jeremy Frank, and Shlomo Zilberstein. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2020.
The Value of Incorporating Social Preferences in Dynamic Ridesharing
Sandhya Saisubramanian, Connor Basich, Shlomo Zilberstein, and Claudia Goldman. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2019.
Minimizing the Negative Side Effects of Planning with Reduced Models
Sandhya Saisubramanian and Shlomo Zilberstein. AAAI Workshop on Artificial Intelligence Safety, 2019.
Safe Reduced Models for Probabilistic Planning
Sandhya Saisubramanian and Shlomo Zilberstein. ICML/IJCAI/AAMAS Workshop on Planning and Learning (PAL), 2018.
Optimizing Electric Vehicle Charging Through Determinization
Sandhya Saisubramanian, Shlomo Zilberstein, and Prashant Shenoy. ICAPS Workshop on Scheduling and Planning Applications (SPARK), 2017.