43 citations · 96 across the 23 of their papers we have counts for
30 papers
Evaluation Beyond Task Performance: Analyzing Concepts in AlphaZero in Hex
Charles Lovering, Jessica Zosa Forde, George Konidaris +2
AlphaZero, an approach to reinforcement learning that couples neural networks and Monte Carlo tree search (MCTS), has produced state-of-the-art strategies for traditional board gam…
Model-based Lifelong Reinforcement Learning with Bayesian Exploration
Haotian Fu, Shangqun Yu, Michael Littman +1
We propose a model-based lifelong reinforcement-learning approach that estimates a hierarchical Bayesian posterior distilling the common structure shared across different tasks. Th…
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills
Seiji Shaw, Devesh K. Jha, Arvind Raghunathan +4
Dynamic movement primitives are widely used for learning skills which can be demonstrated to a robot by a skilled human or controller. While their generalization capabilities and s…
Characterizing the Action-Generalization Gap in Deep Q-Learning
Zhiyuan Zhou, Cameron Allen, Kavosh Asadi +1
We study the action generalization ability of deep Q-learning in discrete action spaces. Generalization is crucial for efficient reinforcement learning (RL) because it allows agent…
Learning Abstract and Transferable Representations for Planning
Steven James, Benjamin Rosman, George Konidaris
We are concerned with the question of how an agent can acquire its own representations from sensory data. We restrict our focus to learning representations for long-term planning,…
Adaptive Online Value Function Approximation with Wavelets
Michael Beukman, Michael Mitchley, Dean Wookey +2
Using function approximation to represent a value function is necessary for continuous and high-dimensional state spaces. Linear function approximation has desirable theoretical gu…