2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.RO2023★ 2 cited
ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents
Tejaswini Manjunath, Mozhgan Navardi, Prakhar Dixit +2
Robots have been successfully used to perform tasks with high precision. In real-world environments with sparse rewards and multiple goals, learning is still a major challenge and…
cs.LG2021★ 1 cited
Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft
Vinicius G. Goecks, Nicholas Waytowich, David Watkins-Valls +1
Real-world tasks of interest are generally poorly defined by human-readable descriptions and have no pre-defined reward signals unless it is defined by a human designer. Conversely…