RLC 2024 Workshop InterpPol Submissions

Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
Quentin Delfosse, Sebastian Sztwiertnia, Mark Rothermel, Wolfgang Stammer, Kristian Kersting
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels
Zhuorui Ye, Stephanie Milani, Fei Fang, Geoffrey J. Gordon
- Published: 07 Jun 2024, Last Modified: 23 Jul 2024
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- Readers: Everyone
OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments
Quentin Delfosse, Jannis Blüml, Bjarne Gregori, Sebastian Sztwiertnia, Kristian Kersting
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning
Quentin Delfosse, Jannis Blüml, Bjarne Gregori, Kristian Kersting
- Published: 07 Jun 2024, Last Modified: 26 Jun 2024
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- Readers: Everyone
Contrastive Sparse Autoencoders for Interpreting Planning of Chess-Playing Agents
Yoann Poupart
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Gradient Boosting Reinforcement Learning
Benjamin Fuhrer, Chen Tessler, Gal Dalal
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Deep Reinforcement Learning with Vector Quantized Encoding
Liang Zhang, Justin Lieffers, Pavithra Shivanna, Adarsh Pyarelal
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Cost Of Interpretability - Blocked Value Iteration
Deepak Badarinath, Agni Orfanoudaki, Soroush Saghafian
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning
Hector Kohler, Quentin Delfosse, Riad Akrour, Kristian Kersting, Philippe Preux
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Learning Quadruped Locomotion Policies Using Logical Rules
David DeFazio, Yohei Hayamizu, Shiqi Zhang
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
Maxime Wabartha, Joelle Pineau
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Transition Noise Facilitates Interpretability
Ronald Parr, Cynthia Rudin, Harry Chen, Zachery Boner, Michal Moshkovitz, Lesia Semenova
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Evaluating the impact of explainable RL on physician decision-making in high-fidelity simulations: insights from eye-tracking metrics
Paul Festor, Myura Nagendran, Matthieu Komorowski, Aldo A. Faisal
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Learning Dynamics and the Geometry of Neural Dynamics in Recurrent Neural Controllers
Ann Huang, Satpreet Harcharan Singh, Kanaka Rajan
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Approximation Algorithms for Observer Aware MDPs
Shuwa Miura, Olivier Buffet, Shlomo Zilberstein
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Understanding biological active sensing behaviors by interpreting learned artificial agent policies
Sonja Johnson-Yu, Satpreet Harcharan Singh, Federico Pedraja, Denis Turcu, Pratyusha Sharma, Naomi Saphra, Nathaniel Sawtell, Kanaka Rajan
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Distilling Reinforcement Learning Policies for Interpretable Robot Locomotion: Gradient Boosting Machines and Symbolic Regression
Fernando Acero, Zhibin Li
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone
Assessing the Interpretability of Programmatic Policies using Large Language Models
Zahra Bashir, Michael Bowling, Levi Lelis
- Published: 07 Jun 2024, Last Modified: 07 Jun 2024
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- Readers: Everyone