Toryn Q. Klassen

Elliot Creager

CoRR, 2023

Planning with Epistemic Preferences.

[BibT_eX]

[DOI]

Christian Muise

Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 2023

Learning Belief Representations for Partially Observable Deep RL.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Epistemic Side Effects: An AI Safety Problem.

[BibT_eX]

[DOI]

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2022

Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines.

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Follow Instructions in Text-Based Games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Resolving Misconceptions about the Plans of Agents via Theory of Mind.

[BibT_eX]

[DOI]

Maayan Shvo

Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

Planning to Avoid Side Effects.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Representing Plausible Beliefs about States, Actions, and Processes.

[BibT_eX]

[DOI]

Toryn Qwyllyn Klassen

PhD thesis, 2021

Be Considerate: Objectives, Side Effects, and Deciding How to Act.

[BibT_eX]

[DOI]

CoRR, 2021

2020

The act of remembering: a study in partially observable reinforcement learning.

[BibT_eX]

[DOI]

Phillip J. K. Christoffersen

Amir-massoud Farahmand

CoRR, 2020

Changing Beliefs about Domain Dynamics in the Situation Calculus.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, 2020

Epistemic Plan Recognition.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Towards the Role of Theory of Mind in Explanation.

[BibT_eX]

[DOI]

Maayan Shvo

Proceedings of the Explainable, Transparent Autonomous Agents and Multi-Agent Systems, 2020

2019

Learning Reward Machines for Partially Observable Reinforcement Learning.

[BibT_eX]

[DOI]

Ethan Waldie

Margarita P. Castro

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning.

[BibT_eX]

[DOI]

Alberto Camacho

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Specifying Plausibility Levels for Iterated Belief Change in the Situation Calculus.

[BibT_eX]

[DOI]

Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Sixteenth International Conference, 2018

Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Teaching Multiple Tasks to an RL Agent using LTL.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Advice-Based Exploration in Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2018

2017

Towards Representing What Readers of Fiction Believe.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Symposium on Commonsense Reasoning, 2017

2015

Towards Tractable Inference for Resource-Bounded Agents.

[BibT_eX]

[DOI]