Josiah Hanna

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 20

Top Topics

Reinforcement Learning

Conditional Mutual Information

Partially Observable Environments

Top Venues

Publications

Jeongyeol Kwon, Liu Yang, Robert D. Nowak, Josiah Hanna
Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments. CoRR (2024)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. NeurIPS (2023)
Brahma S. Pavse, Josiah Hanna
State-Action Similarity-Based Representations for Off-Policy Evaluation. NeurIPS (2023)
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. NeurIPS (2023)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. CoRR (2023)
Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano V. Albrecht, Josiah Hanna
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning. NeurIPS (2022)
Mhairi Dunion, Trevor McInroe, Kevin Luck, Josiah Hanna, Stefano V. Albrecht
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. CoRR (2022)
Chi Zhang, Olga Papaemmanouil, Josiah Hanna
Multi-agent Databases via Independent Learning. CoRR (2022)
Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht
Decoupling Exploration and Exploitation in Reinforcement Learning. CoRR (2021)
Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone
Reducing Sampling Error in Batch Temporal Difference Learning. ICML (2020)
Brahma S. Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, Peter Stone
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics Autom. Lett. 5 (4) (2020)
Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone
Reducing Sampling Error in Batch Temporal Difference Learning. CoRR (2020)
Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone
An Imitation from Observation Approach to Sim-to-Real Transfer. CoRR (2020)
Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. NeurIPS (2020)
Josiah Hanna, Scott Niekum, Peter Stone
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. ICML (2019)
James Ault, Josiah Hanna, Guni Sharon
Learning an Interpretable Traffic Signal Control Policy. CoRR (2019)
Josiah Hanna, Scott Niekum, Peter Stone
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. CoRR (2018)
Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone
Fast and Precise Black and White Ball Detection for RoboCup Soccer. RoboCup (2017)
Katie Genter, Patrick MacAlpine, Jacob Menashe, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone
UT Austin Villa: Project-Driven Research in AI and Robotics. IEEE Intell. Syst. 31 (2) (2016)
Guni Sharon, Josiah Hanna, Tarun Rambha, Michael Albert, Peter Stone, Stephen D. Boyles
Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput. ATT@IJCAI (2016)
Patrick MacAlpine, Josiah Hanna, Jason Liang, Peter Stone
UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions. RoboCup (2015)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. CoRR (2013)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. AAAI (Late-Breaking Developments) (2013)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. UAI (2013)