Josiah Hanna

Orcid: 0000-0002-7411-0398

According to our database1, Josiah Hanna authored at least 51 papers between 2013 and 2024.

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Bibliography

2024
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning.
CoRR, 2024

SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP.
CoRR, 2024

Adaptive Exploration for Data-Efficient General Value Function Evaluations.
CoRR, 2024

Future Prediction Can be a Strong Evidence of Good History Representation in Partially Observable Environments.
CoRR, 2024

SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Scaling Offline Evaluation of Reinforcement Learning Agents through Abstraction.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling.
CoRR, 2023

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning.
CoRR, 2023

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates.
CoRR, 2023

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning.
CoRR, 2023

State-Action Similarity-Based Representations for Off-Policy Evaluation.
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.
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.
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.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Safe Evaluation For Offline Learning: Are We Ready To Deploy?
CoRR, 2022

Multi-agent Databases via Independent Learning.
CoRR, 2022

ReVar: Strengthening policy evaluation via reduced variance sampling.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning.
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.
Proceedings of the Conference on Lifelong Learning Agents, 2022

Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Importance sampling in reinforcement learning with an estimated behavior policy.
Mach. Learn., 2021

Grounded action transformation for sim-to-real reinforcement learning.
Mach. Learn., 2021

Robust On-Policy Data Collection for Data-Efficient Policy Evaluation.
CoRR, 2021

Decoupling Exploration and Exploitation in Reinforcement Learning.
CoRR, 2021

Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction.
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.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret.
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.
IEEE Robotics Autom. Lett., 2020

An Imitation from Observation Approach to Sim-to-Real Transfer.
CoRR, 2020

Quantum-Secure Authentication via Abstract Multi-Agent Interaction.
CoRR, 2020

An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
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.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Stochastic Grounded Action Transformation for Robot Learning in Simulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Reducing Sampling Error in Batch Temporal Difference Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning an Interpretable Traffic Signal Control Policy.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
Proceedings of the 36th International Conference on Machine Learning, 2019

Reducing Sampling Error in Policy Gradient Learning.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Selecting Compliant Agents for Opt-in Micro-Tolling.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Towards a Data Efficient Off-Policy Policy Gradient.
Proceedings of the 2018 AAAI Spring Symposia, 2018

DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Fast and Precise Black and White Ball Detection for RoboCup Soccer.
Proceedings of the RoboCup 2017: Robot World Cup XXI [Nagoya, Japan, July 27-31, 2017]., 2017

Data-Efficient Policy Evaluation Through Behavior Policy Search.
Proceedings of the 34th International Conference on Machine Learning, 2017

Bridging the Gap Between Simulation and Reality.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Grounded Action Transformation for Robot Learning in Simulation.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
UT Austin Villa: Project-Driven Research in AI and Robotics.
IEEE Intell. Syst., 2016

High Confidence Off-Policy Evaluation with Models.
CoRR, 2016

Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput.
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.
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.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013


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