Josiah P. Hanna

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 49

Top Topics

Traffic Signal Control

High Confidence

Reinforcement Learning

Top Venues

Publications

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 (2024)
Nicholas Corrado, Josiah P. Hanna
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates. ICLR (2024)
Josiah P. Hanna
Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction. AAAI (2024)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. AISTATS (2024)
Abhinav Narayan Harish, Larry Heck, Josiah P. Hanna, Zsolt Kira, Andrew Szot
Reinforcement Learning via Auxiliary Task Distillation. CoRR (2024)
Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak
SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP. CoRR (2024)
Arushi Jain, Josiah P. Hanna, Doina Precup
Adaptive Exploration for Data-Efficient General Value Function Evaluations. CoRR (2024)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. CoRR (2023)
Brahma S. Pavse, Josiah P. Hanna
State-Action Similarity-Based Representations for Off-Policy Evaluation. CoRR (2023)
Nicholas E. Corrado, Josiah P. Hanna
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates. CoRR (2023)
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. CoRR (2023)
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)
Brahma S. Pavse, Josiah P. Hanna
Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction. AAAI (2023)
Nicholas E. Corrado, Yuxiao Qu, John U. Balis, Adam Labiosa, Josiah P. Hanna
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning. CoRR (2023)
Nicholas E. Corrado, Josiah P. Hanna
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling. CoRR (2023)
Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna
Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning. CoRR (2023)
Brahma S. Pavse, Josiah P. Hanna
Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction. CoRR (2022)
Lukas Schäfer, Filippos Christianos, Josiah P. Hanna, Stefano V. Albrecht
Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration. AAMAS (2022)
Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon, Josiah P. Hanna
A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret. CoRR (2022)
Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna
Simulation-Acquired Latent Action Spaces for Dynamics Generalization. CoLLAs (2022)
Hager Radi, Josiah P. Hanna, Peter Stone, Matthew E. Taylor
Safe Evaluation For Offline Learning: Are We Ready To Deploy? CoRR (2022)
Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak
ReVar: Strengthening Policy Evaluation via Reduced Variance Sampling. CoRR (2022)
Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak
ReVar: Strengthening policy evaluation via reduced variance sampling. UAI (2022)
Ibrahim Ahmed, Josiah P. Hanna, Elliot Fosong, Stefano V. Albrecht
Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction. PAAMS (2021)
Sheelabhadra Dey, Sumedh Pendurkar, Guni Sharon, Josiah P. Hanna
A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret. IROS (2021)
Josiah P. Hanna, Scott Niekum, Peter Stone
Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. 110 (6) (2021)
Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation. CoRR (2021)
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)
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 (2021)
Josiah P. Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, Peter Stone
Grounded action transformation for sim-to-real reinforcement learning. Mach. Learn. 110 (9) (2021)
Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone
Stochastic Grounded Action Transformation for Robot Learning in Simulation. IROS (2020)
Ibrahim Ahmed, Josiah P. Hanna, Stefano V. Albrecht
Quantum-Secure Authentication via Abstract Multi-Agent Interaction. CoRR (2020)
Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. IROS (2020)
Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, Peter Stone
Reinforced Grounded Action Transformation for Sim-to-Real Transfer. CoRR (2020)
Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, Peter Stone
Stochastic Grounded Action Transformation for Robot Learning in Simulation. CoRR (2020)
James Ault, Josiah P. Hanna, Guni Sharon
Learning an Interpretable Traffic Signal Control Policy. AAMAS (2020)
Josiah P. Hanna, Peter Stone
Reducing Sampling Error in Policy Gradient Learning. AAMAS (2019)
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 (2019)
Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone
Selecting Compliant Agents for Opt-in Micro-Tolling. AAAI (2019)
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)
Josiah P. Hanna, Peter Stone
Towards a Data Efficient Off-Policy Policy Gradient. AAAI Spring Symposia (2018)
Josiah P. Hanna, Peter Stone, Scott Niekum
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAMAS (2017)
Josiah P. Hanna, Peter Stone
Grounded Action Transformation for Robot Learning in Simulation. AAAI (2017)
Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum
Data-Efficient Policy Evaluation Through Behavior Policy Search. ICML (2017)
Josiah P. Hanna
Bridging the Gap Between Simulation and Reality. AAMAS (2017)
Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum
Data-Efficient Policy Evaluation Through Behavior Policy Search. CoRR (2017)
Josiah P. Hanna, Peter Stone, Scott Niekum
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAAI (2017)
Josiah P. Hanna, Peter Stone
Grounded Action Transformation for Robot Learning in Simulation. AAAI (2017)
Josiah P. Hanna, Peter Stone, Scott Niekum
High Confidence Off-Policy Evaluation with Models. CoRR (2016)