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ORCIDToryn Q. Klassen
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Books and Theses
- 2021
[b1]Toryn Qwyllyn Klassen:
Representing Plausible Beliefs about States, Actions, and Processes. University of Toronto, Canada, 2021
Journal Articles
- 2023
- [j2]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: 103989 (2023) - 2022
- [j1]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: 173-208 (2022)
Conference and Workshop Papers
- 2024
- [c20]Parand A. Alamdari, Toryn Q. Klassen, Elliot Creager, Sheila A. McIlraith:
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making. ICML 2024 - 2023
- [c19]Toryn Q. Klassen, Parand Alizadeh Alamdari, Sheila A. McIlraith:
Epistemic Side Effects: An AI Safety Problem. AAMAS 2023: 1797-1801 - [c18]Andrew Wang, Andrew C. Li, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Learning Belief Representations for Partially Observable Deep RL. ICML 2023: 35970-35988 - [c17]Toryn Q. Klassen, Christian Muise, Sheila A. McIlraith:
Planning with Epistemic Preferences. KR 2023: 752-756 - 2022
- [c16]Toryn Q. Klassen, Sheila A. McIlraith, Christian Muise, Jarvis Xu:
Planning to Avoid Side Effects. AAAI 2022: 9830-9839 - [c15]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Resolving Misconceptions about the Plans of Agents via Theory of Mind. ICAPS 2022: 719-729 - [c14]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning. AAMAS 2022: 18-26 - [c13]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 - 2020
- [c12]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Towards the Role of Theory of Mind in Explanation. EXTRAAMAS@AAMAS 2020: 75-93 - [c11]Maayan Shvo, Toryn Q. Klassen, Shirin Sohrabi, Sheila A. McIlraith:
Epistemic Plan Recognition. AAMAS 2020: 1251-1259 - [c10]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Changing Beliefs about Domain Dynamics in the Situation Calculus. KR 2020: 572-581 - 2019
- [c9]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: 6065-6073 - [c8]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: 15497-15508 - 2018
- [c7]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Advice-Based Exploration in Model-Based Reinforcement Learning. Canadian AI 2018: 72-83 - [c6]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Teaching Multiple Tasks to an RL Agent using LTL. AAMAS 2018: 452-461 - [c5]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: 2112-2121 - [c4]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Specifying Plausibility Levels for Iterated Belief Change in the Situation Calculus. KR 2018: 257-266 - 2017
- [c3]Toryn Q. Klassen, Hector J. Levesque, Sheila A. McIlraith:
Towards Representing What Readers of Fiction Believe. COMMONSENSE 2017 - 2015
- [c2]Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque:
Towards Tractable Inference for Resource-Bounded Agents. AAAI Spring Symposia 2015 - 2012
- [c1]Toryn Qwyllyn Klassen, Philipp Woelfel:
Independence of Tabulation-Based Hash Classes. LATIN 2012: 506-517
Informal and Other Publications
- 2024
- [i10]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 abs/2406.00120 (2024) - 2023
- [i9]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 abs/2312.04772 (2023) - 2022
- [i8]Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith:
Learning to Follow Instructions in Text-Based Games. CoRR abs/2211.04591 (2022) - [i7]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 abs/2211.10902 (2022) - 2021
- [i6]Parand Alizadeh Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith:
Be Considerate: Objectives, Side Effects, and Deciding How to Act. CoRR abs/2106.02617 (2021) - [i5]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 abs/2112.09477 (2021) - 2020
- [i4]Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith:
Towards the Role of Theory of Mind in Explanation. CoRR abs/2005.02963 (2020) - [i3]Rodrigo Toro Icarte, Richard Anthony Valenzano, Toryn Q. Klassen, Phillip J. K. Christoffersen, Amir-massoud Farahmand, Sheila A. McIlraith:
The act of remembering: a study in partially observable reinforcement learning. CoRR abs/2010.01753 (2020) - [i2]Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Anthony Valenzano, Sheila A. McIlraith:
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning. CoRR abs/2010.03950 (2020) - 2011
- [i1]Toryn Qwyllyn Klassen, Philipp Woelfel:
Independence of Tabulation-Based Hash Classes. CoRR abs/1112.3323 (2011)
Coauthor Index
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