David Abel


Conference Papers
Toward Improving Solar Panel Efficiency with Reinforcement Learning.
David Abel, Emily Reif, Edward C. Williams, Michael L. Littman.
EnviroInfo 2017.

Near Optimal Behavior via Approximate State Abstraction.
David Abel, D Ellis Hershkowitz, Michael L. Littman.
ICML 2016. arXiv version.

Goal Based Action Priors.
David Abel, D Ellis Hershkowitz, Gabriel Barth-Maron, Stephen Brawner, Kevin O'Farrell, James MacGlashan, Stefanie Tellex.
ICAPS 2015.
Workshops, Symposia, & Extended Abstracts
Improving Solar Panel Efficiency using Reinforcement Learning.
David Abel, Emily Reif, Michael L. Littman.
RLDM 2017.

Agent-Agnostic Human-In-The-Loop Reinforcement Learning.
David Abel, John Salvatier, Andreas Stuhlmüller, Owain Evans.
NIPS Workshop on The Future of Interactive Learning Machines, 2016. arXiv version.

Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains.
David Abel, Alekh Agarwal, Fernando Diaz, Akshay Krishnamurthy, Robert Schapire.
ICML Workshop on Reinforcement Learning and Abstraction, 2016.

Reinforcement Learning as a Framework for Ethical Decision Making.
David Abel, James MacGlashan, Michael L. Littman.
AAAI Workshop on AI, Society, & Ethics, 2016.

Affordances as Transferrable Knowledge for Planning Agents.
Gabriel Barth-Maron, David Abel, James MacGlashan, Stefanie Tellex.
AAAI Symposium on Knowledge and Skill Transfer, 2014.

Toward Affordance-Aware Planning.
David Abel, Gabriel Barth-Maron, James MacGlashan, Stefanie Tellex.
RSS Workshop on Affordances in Vision for Cognitive Robotics, 2014.
Other Works
Latent Attention Networks.
Christopher Grimm, Dilip Arumugam, Siddharth Karamcheti, David Abel, Lawson L.S. Wong, Michael L. Littman.
Preprint, 2017.

Learning to Plan in Complex Stochastic Domains.
David Abel. Advised by Prof. Stefanie Tellex.
Master’s Thesis, Brown University, 2015.