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ORCIDJosiah Hanna
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2020 – today
- 2024
[j5]Josiah P. Hanna
:
Toward the confident deployment of real-world reinforcement learning agents. AI Mag. 45(3): 396-403 (2024)- [c38]Josiah P. Hanna:
Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction. AAAI 2024: 22667 - [c37]Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak:
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. AISTATS 2024: 2962-2970 - [c36]Nicholas Corrado, Josiah P. Hanna:
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates. ICLR 2024 - [c35]Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak:
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP. ICML 2024 - [c34]Brahma S. Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna:
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces. ICML 2024 - [i34]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 abs/2402.07102 (2024) - [i33]Arushi Jain, Josiah P. Hanna, Doina Precup:
Adaptive Exploration for Data-Efficient General Value Function Evaluations. CoRR abs/2405.07838 (2024) - [i32]Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak:
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP. CoRR abs/2406.02165 (2024) - [i31]Subhojyoti Mukherjee, Josiah P. Hanna, Qiaomin Xie, Robert D. Nowak:
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning. CoRR abs/2406.05064 (2024) - [i30]Abhinav Narayan Harish, Larry Heck, Josiah P. Hanna, Zsolt Kira, Andrew Szot:
Reinforcement Learning via Auxiliary Task Distillation. CoRR abs/2406.17168 (2024) - [i29]Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna:
Stable Offline Value Function Learning with Bisimulation-based Representations. CoRR abs/2410.01643 (2024) - 2023
- [c33]Brahma S. Pavse, Josiah P. Hanna:
Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction. AAAI 2023: 9417-9425 - [c32]Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht:
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. ICLR 2023 - [c31]Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht:
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. NeurIPS 2023 - [c30]Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak:
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. NeurIPS 2023 - [c29]Brahma S. Pavse, Josiah Hanna:
State-Action Similarity-Based Representations for Off-Policy Evaluation. NeurIPS 2023 - [i28]Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak:
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. CoRR abs/2301.12357 (2023) - [i27]Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht:
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. CoRR abs/2305.14133 (2023) - [i26]Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna:
Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning. CoRR abs/2306.01896 (2023) - [i25]Nicholas E. Corrado, Josiah P. Hanna:
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates. CoRR abs/2310.17786 (2023) - [i24]Nicholas E. Corrado, Yuxiao Qu, John U. Balis, Adam Labiosa, Josiah P. Hanna:
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning. CoRR abs/2310.18247 (2023) - [i23]Brahma S. Pavse, Josiah P. Hanna:
State-Action Similarity-Based Representations for Off-Policy Evaluation. CoRR abs/2310.18409 (2023) - [i22]Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak:
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. CoRR abs/2311.00327 (2023) - [i21]Nicholas E. Corrado, Josiah P. Hanna:
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling. CoRR abs/2311.08290 (2023) - 2022
- [c28]Lukas Schäfer, Filippos Christianos, Josiah P. Hanna, Stefano V. Albrecht:
Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration. AAMAS 2022: 1146-1154 - [c27]Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna:
Simulation-Acquired Latent Action Spaces for Dynamics Generalization. CoLLAs 2022: 661-682 - [c26]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 - [c25]Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak:
ReVar: Strengthening policy evaluation via reduced variance sampling. UAI 2022: 1413-1422 - [i20]Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak:
ReVar: Strengthening Policy Evaluation via Reduced Variance Sampling. CoRR abs/2203.04510 (2022) - [i19]Chi Zhang, Olga Papaemmanouil, Josiah Hanna:
Multi-agent Databases via Independent Learning. CoRR abs/2205.14323 (2022) - [i18]Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht:
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. CoRR abs/2207.05480 (2022) - [i17]Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon, Josiah P. Hanna:
A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret. CoRR abs/2209.09446 (2022) - [i16]Brahma S. Pavse, Josiah P. Hanna:
Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction. CoRR abs/2212.07486 (2022) - [i15]Hager Radi, Josiah P. Hanna, Peter Stone, Matthew E. Taylor:
Safe Evaluation For Offline Learning: Are We Ready To Deploy? CoRR abs/2212.08302 (2022) - 2021
- [j4]Josiah P. Hanna, Scott Niekum, Peter Stone:
Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. 110(6): 1267-1317 (2021) - [j3]Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, Peter Stone:
Grounded action transformation for sim-to-real reinforcement learning. Mach. Learn. 110(9): 2469-2499 (2021) - [c24]Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon, Josiah P. Hanna:
A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret. IROS 2021: 3485-3491 - [c23]Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht:
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles. IROS 2021: 7044-7051 - [c22]Ibrahim Ahmed, Josiah P. Hanna, Elliot Fosong, Stefano V. Albrecht:
Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction. PAAMS 2021: 14-26 - [i14]Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht:
Decoupling Exploration and Exploitation in Reinforcement Learning. CoRR abs/2107.08966 (2021) - [i13]Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht:
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles. CoRR abs/2108.02530 (2021) - [i12]Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht:
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation. CoRR abs/2111.14552 (2021) - 2020
- [j2]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): 6262-6269 (2020) - [c21]James Ault, Josiah P. Hanna, Guni Sharon:
Learning an Interpretable Traffic Signal Control Policy. AAMAS 2020: 88-96 - [c20]Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone:
Reducing Sampling Error in Batch Temporal Difference Learning. ICML 2020: 7543-7552 - [c19]Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. IROS 2020: 4397-4402 - [c18]Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Stochastic Grounded Action Transformation for Robot Learning in Simulation. IROS 2020: 6106-6111 - [c17]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 - [i11]Ibrahim Ahmed, Josiah P. Hanna, Stefano V. Albrecht:
Quantum-Secure Authentication via Abstract Multi-Agent Interaction. CoRR abs/2007.09327 (2020) - [i10]Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. CoRR abs/2008.01279 (2020) - [i9]Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone:
Stochastic Grounded Action Transformation for Robot Learning in Simulation. CoRR abs/2008.01281 (2020) - [i8]Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone:
An Imitation from Observation Approach to Sim-to-Real Transfer. CoRR abs/2008.01594 (2020) - [i7]Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone:
Reducing Sampling Error in Batch Temporal Difference Learning. CoRR abs/2008.06738 (2020)
2010 – 2019
- 2019
- [c16]Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone:
Selecting Compliant Agents for Opt-in Micro-Tolling. AAAI 2019: 565-572 - [c15]Josiah P. Hanna, Peter Stone:
Reducing Sampling Error in Policy Gradient Learning. AAMAS 2019: 1016-1024 - [c14]Josiah Hanna, Scott Niekum, Peter Stone:
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. ICML 2019: 2605-2613 - [i6]Brahma S. Pavse, Faraz Torabi, Josiah P. Hanna, Garrett Warnell, Peter Stone:
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. CoRR abs/1906.07372 (2019) - [i5]James Ault, Josiah Hanna, Guni Sharon:
Learning an Interpretable Traffic Signal Control Policy. CoRR abs/1912.11023 (2019) - 2018
- [c13]Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, Yeng Chai Soh:
DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation. AAAI 2018: 757-765 - [c12]Josiah P. Hanna, Peter Stone:
Towards a Data Efficient Off-Policy Policy Gradient. AAAI Spring Symposia 2018 - [i4]Josiah Hanna, Scott Niekum, Peter Stone:
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. CoRR abs/1806.01347 (2018) - 2017
- [c11]Josiah P. Hanna, Peter Stone:
Grounded Action Transformation for Robot Learning in Simulation. AAAI 2017: 3834-3840 - [c10]Josiah P. Hanna, Peter Stone:
Grounded Action Transformation for Robot Learning in Simulation. AAAI 2017: 4931-4932 - [c9]Josiah P. Hanna, Peter Stone, Scott Niekum:
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAAI 2017: 4933-4934 - [c8]Josiah P. Hanna, Peter Stone, Scott Niekum:
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAMAS 2017: 538-546 - [c7]Josiah P. Hanna:
Bridging the Gap Between Simulation and Reality. AAMAS 2017: 1834-1835 - [c6]Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum:
Data-Efficient Policy Evaluation Through Behavior Policy Search. ICML 2017: 1394-1403 - [c5]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: 45-58 - [i3]Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum:
Data-Efficient Policy Evaluation Through Behavior Policy Search. CoRR abs/1706.03469 (2017) - 2016
- [j1]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): 94-101 (2016) - [c4]Guni Sharon, Josiah Hanna, Tarun Rambha, Michael Albert, Peter Stone, Stephen D. Boyles:
Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput. ATT@IJCAI 2016 - [i2]Josiah P. Hanna, Peter Stone, Scott Niekum:
High Confidence Off-Policy Evaluation with Models. CoRR abs/1606.06126 (2016) - 2015
- [c3]Patrick MacAlpine, Josiah Hanna, Jason Liang, Peter Stone:
UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions. RoboCup 2015: 118-131 - 2013
- [c2]Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna:
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. AAAI (Late-Breaking Developments) 2013 - [c1]Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna:
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. UAI 2013 - [i1]Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna:
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. CoRR abs/1309.6856 (2013)
Coauthor Index
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last updated on 2024-11-08 20:30 CET by the dblp team
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