14 citations · 32 across the 7 of their papers we have counts for
7 papers
Hakken: Predicting future discoveries to fill the gaps in today's knowledge
Tarek R. Besold, Uchenna Akujuobi, Pablo Sanchez +21
We present Hakken, a domain-agnostic prediction and explanation system performing knowledge prediction, i.e., growing scientific knowledge by establishing novel relationships, ones…
Composing Efficient, Robust Tests for Policy Selection
Dustin Morrill, Thomas J. Walsh, Daniel Hernandez +2
Modern reinforcement learning systems produce many high-quality policies throughout the learning process. However, to choose which policy to actually deploy in the real world, they…
Event Tables for Efficient Experience Replay
Varun Kompella, Thomas J. Walsh, Samuel Barrett +2
Experience replay (ER) is a crucial component of many deep reinforcement learning (RL) systems. However, uniform sampling from an ER buffer can lead to slow convergence and unstabl…
Value Function Decomposition for Iterative Design of Reinforcement Learning Agents
James MacGlashan, Evan Archer, Alisa Devlic +4
Designing reinforcement learning (RL) agents is typically a difficult process that requires numerous design iterations. Learning can fail for a multitude of reasons, and standard R…
Reinforcement Learning for Optimization of COVID-19 Mitigation policies
Varun Kompella, Roberto Capobianco, Stacy Jong +5
The year 2020 has seen the COVID-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world are faced with the challenge of protecting…
Analysis and Observations from the First Amazon Picking Challenge
Nikolaus Correll, Kostas E. Bekris, Dmitry Berenson +7
This paper presents a overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to desi…