Toryn Q. Klassen

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 28

Top Topics

Partially Observable

Formal Languages

Reinforcement Learning

Plan Recognition

Top Venues

Publications

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)
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)
Toryn Q. Klassen, Parand Alizadeh Alamdari, Sheila A. McIlraith
Epistemic Side Effects: An AI Safety Problem. AAMAS (2023)
Toryn Q. Klassen, Christian Muise, Sheila A. McIlraith
Planning with Epistemic Preferences. KR (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)
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)
Maayan Shvo, Toryn Q. Klassen, Sheila A. McIlraith
Resolving Misconceptions about the Plans of Agents via Theory of Mind. ICAPS (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)
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)
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)
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)
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, Toryn Q. Klassen, Sheila A. McIlraith
Towards the Role of Theory of Mind in Explanation. 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)
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, 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, 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)
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)
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)
Toryn Q. Klassen, Hector J. Levesque, Sheila A. McIlraith
Towards Representing What Readers of Fiction Believe. COMMONSENSE (2017)
Toryn Q. Klassen, Sheila A. McIlraith, Hector J. Levesque
Towards Tractable Inference for Resource-Bounded Agents. AAAI Spring Symposia (2015)