Sheila A. McIlraith

ORCID

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 99

Top Venues

Publications

Diane Horton, David Liu, Sheila A. McIlraith, Steven Coyne, Nina Wang
Do Embedded Ethics Modules Have Impact Beyond the Classroom? SIGCSE (1) (2024)
Eric Horvitz, Vincent Conitzer, Sheila A. McIlraith, Peter Stone
Now, Later, and Lasting: 10 Priorities for AI Research, Policy, and Practice. Commun. ACM 67 (6) (2024)
Andrew C. Li, Zizhao Chen, Toryn Q. Klassen, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith
Reward Machines for Deep RL in Noisy and Uncertain Environments. CoRR (2024)
Christian Muise, Sheila A. McIlraith, J. Christopher Beck
PRP Rebooted: Advancing the State of the Art in FOND Planning. AAAI (2024)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
Neural Sequence Generation with Constraints via Beam Search with Cuts: A Case Study on VRP. SOCS (2024)
Eric Horvitz, Vincent Conitzer, Sheila A. McIlraith, Peter Stone
Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice. CoRR (2024)
Parand Alizadeh Alamdari, Toryn Q. Klassen, Elliot Creager, Sheila A. McIlraith
Remembering to Be Fair: On Non-Markovian Fairness in Sequential Decision Making (Preliminary Report). CoRR (2023)
Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. CoRR (2023)
Toryn Q. Klassen, Parand Alizadeh Alamdari, Sheila A. McIlraith
Epistemic Side Effects: An AI Safety Problem. AAMAS (2023)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
Optimal Decision Trees For Interpretable Clustering with Constraints. CoRR (2023)
Christian Muise, Sheila A. McIlraith, J. Christopher Beck
PRP Rebooted: Advancing the State of the Art in FOND Planning. CoRR (2023)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
SAT-based optimal classification trees for non-binary data. Constraints An Int. J. 28 (2) (2023)
Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. NeurIPS (2023)
Diane Horton, David Liu, Sheila A. McIlraith, Nina Wang
Is More Better When Embedding Ethics in CS Courses? SIGCSE (1) (2023)
Phillip J. K. Christoffersen, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior. CoRR (2023)
Toryn Q. Klassen, Christian Muise, Sheila A. McIlraith
Planning with Epistemic Preferences. KR (2023)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
SAT-Based Learning of Compact Binary Decision Diagrams for Classification. CP (2023)
Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Learning Belief Representations for Partially Observable Deep RL. ICML (2023)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Margarita P. Castro, Ethan Waldie, Sheila A. McIlraith
Learning reward machines: A study in partially observable reinforcement learning. Artif. Intell. 323 (2023)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
Optimal Decision Trees For Interpretable Clustering with Constraints. IJCAI (2023)
Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith
Learning to Follow Instructions in Text-Based Games. NeurIPS (2022)
Diane Horton, Sheila A. McIlraith, Nina Wang, Maryam Majedi, Emma McClure, Benjamin Wald
Embedding Ethics in Computer Science Courses: Does it Work? SIGCSE (1) (2022)
Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith
Resolving Misconceptions about the Plans of Agents via Theory of Mind. ICAPS (2022)
Jorge A. Baier, Sheila A. McIlraith
Knowledge-based programs as building blocks for planning. Artif. Intell. 303 (2022)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. J. Artif. Intell. Res. 73 (2022)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. CoRR (2022)
Andrew C. Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith
Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks. CoRR (2022)
Fredrik Heintz, Gerhard Lakemeyer, Sheila A. McIlraith
Cognitive Robotics (Dagstuhl Seminar 22391). Dagstuhl Reports 12 (9) (2022)
Maayan Shvo, Ruthrash Hari, Ziggy O'Reilly, Sophia Abolore, Sze-Yuh Nina Wang, Sheila A. McIlraith
Proactive Robotic Assistance via Theory of Mind. IROS (2022)
Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith
Learning to Follow Instructions in Text-Based Games. CoRR (2022)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. NeurIPS (2022)
Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg
Efficient multi-agent epistemic planning: Teaching planners about nested belief. Artif. Intell. 302 (2022)
Andrew C. Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines. CoRR (2022)
Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. AAMAS (2022)
Toryn Q. Klassen, Sheila A. McIlraith, Christian Muise, Jarvis Xu
Planning to Avoid Side Effects. AAAI (2022)
Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. Canadian Conference on AI (2021)
Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning. CoRR (2021)
Christian Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg
Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief. CoRR (2021)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
Planning from Pixels using Inverse Dynamics Models. ICLR (2021)
Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. ICML (2021)
Pouya Shati, Eldan Cohen, Sheila A. McIlraith
SAT-Based Approach for Learning Optimal Decision Trees with Non-Binary Features. CP (2021)
Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith
Be Considerate: Objectives, Side Effects, and Deciding How to Act. CoRR (2021)
Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Interpretable Sequence Classification via Discrete Optimization. AAAI (2021)
Pashootan Vaezipoor, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
LTL2Action: Generalizing LTL Instructions for Multi-Task RL. CoRR (2021)
Eldan Cohen, Richard Anthony Valenzano, Sheila A. McIlraith
Type-WA*: Using Exploration in Bounded Suboptimal Planning. IJCAI (2021)
Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan D. Jepson, Sheila A. McIlraith
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning. CoRR (2021)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
Planning from Pixels using Inverse Dynamics Models. CoRR (2020)
Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith
Towards the Role of Theory of Mind in Explanation. CoRR (2020)
Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith
Interpretable Sequence Classification via Discrete Optimization. CoRR (2020)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. CoRR (2020)
Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque
Changing Beliefs about Domain Dynamics in the Situation Calculus. KR (2020)
León Illanes, Xi Yan, Rodrigo Toro Icarte, Sheila A. McIlraith
Symbolic Plans as High-Level Instructions for Reinforcement Learning. ICAPS (2020)
Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith
The act of remembering: a study in partially observable reinforcement learning. CoRR (2020)
Maayan Shvo, Sheila A. McIlraith
Active Goal Recognition. AAAI (2020)
Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith
Towards the Role of Theory of Mind in Explanation. EXTRAAMAS@AAMAS (2020)
Maayan Shvo, Toryn Q. Klassen, Shirin Sohrabi, Sheila A. McIlraith
Epistemic Plan Recognition. AAMAS (2020)
Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith
Learning Reward Machines for Partially Observable Reinforcement Learning. NeurIPS (2019)
Alberto Camacho, Sheila A. McIlraith
Towards Neural-Guided Program Synthesis for Linear Temporal Logic Specifications. CoRR (2019)
Maayan Shvo, Sheila A. McIlraith
Towards Empathetic Planning. CoRR (2019)
Alberto Camacho, Sheila A. McIlraith
Strong Fully Observable Non-Deterministic Planning with LTL and LTLf Goals. IJCAI (2019)
Rodrigo Toro Icarte, León Illanes, Margarita P. Castro, André A. Ciré, Sheila A. McIlraith, J. Christopher Beck
Training Binarized Neural Networks Using MIP and CP. CP (2019)
León Illanes, Sheila A. McIlraith
Generalized Planning via Abstraction: Arbitrary Numbers of Objects. AAAI (2019)
Alberto Camacho, Sheila A. McIlraith
Learning Interpretable Models Expressed in Linear Temporal Logic. ICAPS (2019)
Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith
Towards a Unified View of AI Planning and Reactive Synthesis. ICAPS (2019)
Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning. IJCAI (2019)
Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith
Finite LTL Synthesis with Environment Assumptions and Quality Measures. CoRR (2018)
Alberto Camacho, Jorge A. Baier, Christian J. Muise, Sheila A. McIlraith
Finite LTL Synthesis as Planning. ICAPS (2018)
Maayan Shvo, Shirin Sohrabi, Sheila A. McIlraith
An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem. Canadian Conference on AI (2018)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Advice-Based Exploration in Model-Based Reinforcement Learning. Canadian Conference on AI (2018)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning. ICML (2018)
Alberto Camacho, Jorge A. Baier, Christian J. Muise, Sheila A. McIlraith
Synthesizing Controllers: On the Correspondence Between LTL Synthesis and Non-deterministic Planning. Canadian Conference on AI (2018)
Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque
Specifying Plausibility Levels for Iterated Belief Change in the Situation Calculus. KR (2018)
Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith
Teaching Multiple Tasks to an RL Agent using LTL. AAMAS (2018)
Alberto Camacho, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith
LTL Realizability via Safety and Reachability Games. IJCAI (2018)
Alberto Camacho, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith
SynKit: LTL Synthesis as a Service. IJCAI (2018)
Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39 (4) (2018)
Alberto Camacho, Meghyn Bienvenu, Sheila A. McIlraith
Finite LTL Synthesis with Environment Assumptions and Quality Measures. KR (2018)
Chitta Baral, Thomas Bolander, Hans van Ditmarsch, Sheila A. McIlraith
Epistemic Planning (Dagstuhl Seminar 17231). Dagstuhl Reports 7 (6) (2017)
Toryn Q. Klassen, Hector J. Levesque, Sheila A. McIlraith
Towards Representing What Readers of Fiction Believe. COMMONSENSE (2017)
Leon Illanes, Sheila A. McIlraith
Numeric Planning via Abstraction and Policy Guided Search. IJCAI (2017)
Sheila A. McIlraith
Plan and Program Synthesis: A New Look at Some Old Problems (Invited Talk). TIME (2017)
Brent Mombourquette, Christian J. Muise, Sheila A. McIlraith
Logical Filtering and Smoothing: State Estimation in Partially Observable Domains. AAAI (2017)
Maayan Shvo, Shirin Sohrabi, Sheila A. McIlraith
An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem (Preliminary Report). AAAI Workshops (2017)
Alberto Camacho, Eleni Triantafillou, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith
Non-Deterministic Planning with Temporally Extended Goals: LTL over Finite and Infinite Traces. AAAI (2017)
Alberto Camacho, Oscar Chen, Scott Sanner, Sheila A. McIlraith
Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping. SOCS (2017)
Brent Mombourquette, Christian J. Muise, Sheila A. McIlraith
Belief State Estimation for Planning via Approximate Logical Filtering and Smoothing. KnowProS@IJCAI (2016)
Leon Illanes, Sheila A. McIlraith
Numeric Planning via Search Space Abstraction. KnowProS@IJCAI (2016)
Alberto Camacho, Sheila A. McIlraith
Strong-Cyclic Planning when Fairness is Not a Valid Assumption. KnowProS@IJCAI (2016)
Christian J. Muise, J. Christopher Beck, Sheila A. McIlraith
Optimal Partial-Order Plan Relaxation via MaxSAT. J. Artif. Intell. Res. 57 (2016)
Young Yoon, Nathan Robinson, Vinod Muthusamy, Sheila A. McIlraith, Hans-Arno Jacobsen
Planning the transformation of overlays. SAC (2016)
Leon Illanes, Sheila A. McIlraith
Numeric Planning via Search Space Abstraction (Extended Abstract). SOCS (2016)
Roy Luo, Richard Anthony Valenzano, Yi Li, J. Christopher Beck, Sheila A. McIlraith
Using Metric Temporal Logic to Specify Scheduling Problems. KR (2016)
Alberto Camacho, Eleni Triantafillou, Christian J. Muise, Jorge A. Baier, Sheila A. McIlraith
Non-Deterministic Planning with Temporally Extended Goals: Completing the Story for Finite and Infinite LTL (Amended Version). KnowProS@IJCAI (2016)
Alberto Camacho, Christian J. Muise, Sheila A. McIlraith
From FOND to Robust Probabilistic Planning: Computing Compact Policies that Bypass Avoidable Deadends. ICAPS (2016)
Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque
Towards Tractable Inference for Resource-Bounded Agents. AAAI Spring Symposia (2015)
Torsten Hahmann, Sheila A. McIlraith
Towards Ontologies in Variation. AAAI Spring Symposia (2015)
Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36 (1) (2015)
Christian J. Muise, Vaishak Belle, Paolo Felli, Sheila A. McIlraith, Tim Miller, Adrian R. Pearce, Liz Sonenberg
Planning Over Multi-Agent Epistemic States: A Classical Planning Approach. AAAI (2015)
Young Yoon, Nathan Robinson, Vinod Muthusamy, Sheila A. McIlraith, Hans-Arno Jacobsen
Towards Planning the Transformation of Overlays. ICDCS (2015)
Christian J. Muise, Sheila A. McIlraith, Vaishak Belle
Non-Deterministic Planning With Conditional Effects. ICAPS (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sheila A. McIlraith