2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
IPPO Learns the Game, Not the Team: A Study on Generalization in Heterogeneous Agent Teams
Ryan LeRoy, Jack Kolb
Multi-Agent Reinforcement Learning (MARL) is commonly deployed in settings where agents are trained via self-play with homogeneous teammates, often using parameter sharing and a si…
The Effects of Robot Motion on Comfort Dynamics of Novice Users in Close-Proximity Human-Robot Interaction
Pierce Howell, Jack Kolb, Yifan Liu +1
Effective and fluent close-proximity human-robot interaction requires understanding how humans get habituated to robots and how robot motion affects human comfort. While prior work…
Constrained Reinforcement Learning for Dexterous Manipulation
Abhineet Jain, Jack Kolb, Harish Ravichandar
Existing learning approaches to dexterous manipulation use demonstrations or interactions with the environment to train black-box neural networks that provide little control over h…
Evaluating the Effectiveness of Corrective Demonstrations and a Low-Cost Sensor for Dexterous Manipulation
Abhineet Jain, Jack Kolb, J. M. Abbess +1
Imitation learning is a promising approach to help robots acquire dexterous manipulation capabilities without the need for a carefully-designed reward or a significant computationa…