25 citations · 57 across the 4 of their papers we have counts for
4 papers
Coachable agents for interactive gameplay
Roberto Capobianco, Harm van Seijen, Nolan D. Bard +38
Reinforcement learning has proven to be a valuable tool in the creation of advanced AI and robotic systems, contributing to everything from game playing to robotics to foundation m…
Reward-Respecting Subtasks for Model-Based Reinforcement Learning
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland +4
To achieve the ambitious goals of artificial intelligence, reinforcement learning must include planning with a model of the world that is abstract in state and time. Deep learning…
The Effect of Planning Shape on Dyna-style Planning in High-dimensional State Spaces
G. Zacharias Holland, Erin J. Talvitie, Michael Bowling
Dyna is a fundamental approach to model-based reinforcement learning (MBRL) that interleaves planning, acting, and learning in an online setting. In the most typical application of…
Multi-step Reinforcement Learning: A Unifying Algorithm
Kristopher De Asis, J. Fernando Hernandez-Garcia, G. Zacharias Holland +1
Unifying seemingly disparate algorithmic ideas to produce better performing algorithms has been a longstanding goal in reinforcement learning. As a primary example, TD() elegant…