1 citations · 2 across the 4 of their papers we have counts for
4 papers
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
Evan Zheran Liu, Sahaana Suri, Tong Mu +2
Whereas machine learning models typically learn language by directly training on language tasks (e.g., next-word prediction), language emerges in human children as a byproduct of s…
Solving Dynamic Principal-Agent Problems with a Rationally Inattentive Principal
Tong Mu, Stephan Zheng, Alexander Trott
Principal-Agent (PA) problems describe a broad class of economic relationships characterized by misaligned incentives and asymmetric information. The Principal's problem is to find…
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning
Tong Mu, Georgios Theocharous, David Arbour +1
Online reinforcement learning (RL) algorithms are often difficult to deploy in complex human-facing applications as they may learn slowly and have poor early performance. To addres…
PLOTS: Procedure Learning from Observations using Subtask Structure
Tong Mu, Karan Goel, Emma Brunskill
In many cases an intelligent agent may want to learn how to mimic a single observed demonstrated trajectory. In this work we consider how to perform such procedural learning from o…