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Publications
In Journals:

In Books:

In Conferences:
  • Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, Sarah Keren. Deep Reinforcement Learning Explanation via Model Transforms. In the Proceedings  of The Conference on Neural Information Processing Systems  (NeurIPS) 2022 (also appeared in the NeurIPS DRL Workshop 2021).
     

  • Kevin C. Gall, Wheeler Ruml, Sarah Keren. Active Goal Recognition Design. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), August 2021
     

  • Sarah Keren, Gerard Canal, and Michael Cashmore. Task-Aware Waypoint Sampling for Planning Robots. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), July 2021 (to appear). Also to appear at the AAAI 2021 Spring Symposium on Machine Learning for Mobile Robot Navigation in the Wild.
     

  • Anagha Kulkarni, Sarath Sreedharan, Sarah Keren, Tathagata Chakrabort, David Smith, and Subbarao Kambhampati. Designing Environments Conducive to Interpretable Robot Behavior. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.
     

  • Sarah Keren, Sara Bernardini, Kofi Kwapong, and David Parkes.  Reasoning About Plan Robustness Versus Plan Cost for Partially Informed Agents.  In Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (KR), September 2020. Presentation Video.
     

  • Sarah Keren, Avigdor Gal, and Erez Karpas.  Goal Recognition Design - Survey. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2020 
     

  • Christabel Wayllace, Sarah Keren, William Yeoh, Avigdor Gal, and Erez Karpas. Accounting for Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map. In Proceedings of the European Conference on Artificial Intelligence (ECAI 2020), June 2020.
     

  • Sarah Keren, Haifeng Xu, Kofi Kwapong, David Parkes, and Barbara Grosz. Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents. In Proceedings of the Conference of the Association for the Advancement of Artificial Intelligence (AAAI), February 2020 
     
  • Sarah Keren, Luis Pineda, Avigdor Gal, Erez Karpas, and Shlomo Zilberstein. Efficient Heuristic Search for Optimal Environment Redesign. In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS 2019), June 2019 
     
  • Sarah Keren, Avigdor Gal, and Erez Karpas. Strong stubborn sets for efficient goal recognition design. InProceedings of the International Conference on Automated Planning and Scheduling (ICAPS 2018), June 2018. also appeared in AAAI 2018 Workshop on Plan, Activity, and Intent Recognition (PAIR 2018).
     

  • Sarah Keren, Luis Pineda, Avigdor Gal, Erez Karpas, and Shlomo Zilberstein.
    Equi-reward Utility Maxi
    mizing Design in Stochastic Environments. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, August 2017.

     

  • Sarah Keren, Avigdor Gal, and Erez Karpas. Privacy preserving plans in partially observable environments. In Proceedings of the International Joint Conference on Artificial  Intelligence (IJCAI 2016), NYC, July 2016.
     

  • Sarah Keren, Avigdor Gal, and Erez Karpas. Goal recognition design with non-observable actions. In Proceedings of the Conference of the American Association of Artificial  Intelligence (AAAI 2016), February 2016. Also appeared in ICAPS Workshop on Heuristic Search in Domain-independent Planning (HSDIP 2015).
     

  • Sarah Keren, Avigdor Gal, and Erez Karpas. Goal recognition design for non-optimal agents.  In Proceedings of the Conference of the Association for the Advancement of Artificial Intelligence (AAAI), January 2015 
     

  • Sarah Keren, Avigdor Gal, and Erez Karpas. Goal recognition design. In Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
    Honorable Mention for the Outstanding Paper Award

In Workshops:

  • Ofir Abu,  Matthias Gerstgrasser, Jeffrey Rosenschein, and Sarah Keren.  Promoting Resilience of Multi-Agent Reinforcement Learning via Confusion-Based CommunicationIn the NeurIPS Workshop on Learning in Presence of Strategic Behavior and Learning and Decision-Making with Strategic Feedback and the NeurIPS Workshop on Cooperative-AI. December 2021.
     

  • Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, Sarah Keren. Deep Reinforcement Learning Explanation via Model Transforms. In the NeurIPS Workshop on Deep Reinforcement Learning. December 2021.
     

  • Sarah Keren, Gopal K. Vashishtha, and David Parkes. Reinforcement Learning Design. In the ICAPS 2019 Workshop on Reasoning about Actions and Processes: Highlights of Recent Advances (RAC-ICAPS 2019)
     

  • Anagha Kulkarni, Sarath Sreedharan, Sarah Keren, Tathagata Chakraborti, and Subbarao Kambhampati Design for Interpretability. In the ICAPS 2019 Workshop on Explainable Planning (XAIP-ICAPS 2019)

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