4 citations · 4 across the 4 of their papers we have counts for
4 papers
When to Plan: Learning to Select Between Reactive Control and Deliberative Planning
Adam Labiosa, Josiah P. Hanna
It has long been recognized that humans have the ability to switch between fast, reactive decision-making and slower, deliberative planning. In this paper, we study the question of…
Multi-Robot Collaboration through Reinforcement Learning and Abstract Simulation
Adam Labiosa, Josiah P. Hanna
Teams of people coordinate to perform complex tasks by forming abstract mental models of world and agent dynamics. The use of abstract models contrasts with much recent work in rob…
Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer
Adam Labiosa, Zhihan Wang, Siddhant Agarwal +10
Robot decision-making in partially observable, real-time, dynamic, and multi-agent environments remains a difficult and unsolved challenge. Model-free reinforcement learning (RL) i…
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning
Nicholas E. Corrado, Yuxiao Qu, John U. Balis +2
In offline reinforcement learning (RL), an RL agent learns to solve a task using only a fixed dataset of previously collected data. While offline RL has been successful in learning…