104 citations · 224 across the 5 of their papers we have counts for
3 papers · 1 filter
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…
Environment-Independent Task Specifications via GLTL
Michael L. Littman, Ufuk Topcu, Jie Fu +3
We propose a new task-specification language for Markov decision processes that is designed to be an improvement over reward functions by being environment independent. The languag…
Interactive Learning from Policy-Dependent Human Feedback
James MacGlashan, Mark K Ho, Robert Loftin +5
This paper investigates the problem of interactively learning behaviors communicated by a human teacher using positive and negative feedback. Much previous work on this problem has…