Edinburgh Research Explorer

Josiah Hanna

Research Associate

Biography

Josiah Hanna is a Research Associate in the School of Informatics at the University of Edinburgh. He received his Ph.D. in the Computer Science Department at the University of Texas at Austin advised by Professor Peter Stone. Prior to attending UT Austin, he completed his B.S. in computer science and mathematics at the University of Kentucky advised by Professor Judy Goldsmith. As a graduate student, Josiah was an NSF Graduate Research Fellow and an IBM PhD Fellow. In August of 2021 he is joining the faculty of the Computer Science Department at the University of Wisconsin-Madison.

His research interests lie in artificial intelligence and machine learning, seeking to develop algorithms that allow autonomous agents to learn from small amounts of data. In particular, he studies reinforcement learning and methods to increase data efficiency of reinforcement learning algorithms.

Qualifications

B.S. in Computer Science and Mathematics, University of Kentucky

Ph.D. in Computer Science, University of Texas at Austin

Research Interests

I study a branch of machine learning called reinforcement learning (RL). Reinforcement learning allows autonomous agents to learn to complete sequential decision making tasks given only a reward signal and interaction with their environment. The goal of my research is to develop and apply reinforcement learning algorithms that are effective with a limited amount of time interacting with a task. My long-term research goal is to develop AI systems that can quickly master a new task with a small number of attempts at the task.

Research outputs

  1. Importance Sampling Policy Evaluation with an Estimated Behavior Policy

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  2. Selecting Compliant Agents for Opt-in Microtolling

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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

    Research output: Contribution to conferencePosterpeer-review

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