Josiah Hanna

According to our database, Josiah Hanna authored at least 54 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Reinforcement Learning via Auxiliary Task Distillation.

Abhinav Narayan Harish, Larry Heck, Josiah P. Hanna, Zsolt Kira, Andrew Szot

CoRR, 2024

Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning.

Subhojyoti Mukherjee, Josiah P. Hanna, Qiaomin Xie, Robert D. Nowak

CoRR, 2024

Adaptive Exploration for Data-Efficient General Value Function Evaluations.

Arushi Jain, Josiah P. Hanna, Doina Precup

CoRR, 2024

Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments.

Jeongyeol Kwon, Liu Yang, Robert D. Nowak, Josiah Hanna

CoRR, 2024

Toward the confident deployment of real-world reinforcement learning agents.

Josiah P. Hanna

AI Mag., 2024

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces.

Brahma S. Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP.

Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates.

Nicholas Corrado, Josiah P. Hanna

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits.

Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction.

Josiah P. Hanna

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling.

Nicholas E. Corrado, Josiah P. Hanna

CoRR, 2023

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning.

Nicholas E. Corrado, Yuxiao Qu, John U. Balis, Adam Labiosa, Josiah P. Hanna

CoRR, 2023

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning.

Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna

CoRR, 2023

State-Action Similarity-Based Representations for Off-Policy Evaluation.

Brahma S. Pavse, Josiah Hanna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-task Representation Learning for Pure Exploration in Bilinear Bandits.

Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning.

Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning.

Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction.

Brahma S. Pavse, Josiah P. Hanna

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Safe Evaluation For Offline Learning: Are We Ready To Deploy?

Hager Radi, Josiah P. Hanna, Peter Stone, Matthew E. Taylor

CoRR, 2022

Multi-agent Databases via Independent Learning.

Chi Zhang, Olga Papaemmanouil, Josiah Hanna

CoRR, 2022

ReVar: Strengthening policy evaluation via reduced variance sampling.

Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning.

Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano V. Albrecht, Josiah Hanna

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

Simulation-Acquired Latent Action Spaces for Dynamics Generalization.

Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna

Proceedings of the Conference on Lifelong Learning Agents, 2022

Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration.

Lukas Schäfer, Filippos Christianos, Josiah P. Hanna, Stefano V. Albrecht

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

2021

Importance sampling in reinforcement learning with an estimated behavior policy.

Josiah P. Hanna, Scott Niekum, Peter Stone

Mach. Learn., 2021

Grounded action transformation for sim-to-real reinforcement learning.

Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, Peter Stone

Mach. Learn., 2021

Robust On-Policy Data Collection for Data-Efficient Policy Evaluation.

Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht

CoRR, 2021

Decoupling Exploration and Exploitation in Reinforcement Learning.

Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht

CoRR, 2021

Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction.

Ibrahim Ahmed, Josiah P. Hanna, Elliot Fosong, Stefano V. Albrecht

Proceedings of the Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection, 2021

Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles.

Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret.

Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon, Josiah P. Hanna

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020

RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.

Brahma S. Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, Peter Stone

IEEE Robotics Autom. Lett., 2020

An Imitation from Observation Approach to Sim-to-Real Transfer.

Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone

CoRR, 2020

Quantum-Secure Authentication via Abstract Multi-Agent Interaction.

Ibrahim Ahmed, Josiah P. Hanna, Stefano V. Albrecht

CoRR, 2020

An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.

Siddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reinforced Grounded Action Transformation for Sim-to-Real Transfer.

Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Stochastic Grounded Action Transformation for Robot Learning in Simulation.

Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Reducing Sampling Error in Batch Temporal Difference Learning.

Brahma S. Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning an Interpretable Traffic Signal Control Policy.

James Ault, Josiah P. Hanna, Guni Sharon

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

2019

Importance Sampling Policy Evaluation with an Estimated Behavior Policy.

Josiah Hanna, Scott Niekum, Peter Stone

Proceedings of the 36th International Conference on Machine Learning, 2019

Reducing Sampling Error in Policy Gradient Learning.

Josiah P. Hanna, Peter Stone

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Selecting Compliant Agents for Opt-in Micro-Tolling.

Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Towards a Data Efficient Off-Policy Policy Gradient.

Josiah P. Hanna, Peter Stone

Proceedings of the 2018 AAAI Spring Symposia, 2018

DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.

Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, Yeng Chai Soh

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Fast and Precise Black and White Ball Detection for RoboCup Soccer.

Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone

Proceedings of the RoboCup 2017: Robot World Cup XXI [Nagoya, Japan, July 27-31, 2017]., 2017

Data-Efficient Policy Evaluation Through Behavior Policy Search.

Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum

Proceedings of the 34th International Conference on Machine Learning, 2017

Bridging the Gap Between Simulation and Reality.

Josiah P. Hanna

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.

Josiah P. Hanna, Peter Stone, Scott Niekum

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Grounded Action Transformation for Robot Learning in Simulation.

Josiah P. Hanna, Peter Stone

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

UT Austin Villa: Project-Driven Research in AI and Robotics.

Katie Genter, Patrick MacAlpine, Jacob Menashe, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, Peter Stone

IEEE Intell. Syst., 2016

High Confidence Off-Policy Evaluation with Models.

Josiah P. Hanna, Peter Stone, Scott Niekum

CoRR, 2016

Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput.

Guni Sharon, Josiah Hanna, Tarun Rambha, Michael Albert, Peter Stone, Stephen D. Boyles

Proceedings of the Ninth International Workshop on Agents in Traffic and Transportation (ATT 2016) co-located with the 25th International Joint Conference On Artificial Intelligence (IJCAI 2016), 2016

2015

UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.

Patrick MacAlpine, Josiah Hanna, Jason Liang, Peter Stone

Proceedings of the RoboCup 2015: Robot World Cup XIX [papers from the 19th Annual RoboCup International Symposium, 2015

2013

Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes.

Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013