1 citations · 1 across the 4 of their papers we have counts for
4 papers
L3M+P: Lifelong Planning with Large Language Models
Krish Agarwal, Yuqian Jiang, Jiaheng Hu +2
By combining classical planning methods with large language models (LLMs), recent research such as LLM+P has enabled agents to plan for general tasks given in natural language. How…
Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks
Viraj Joshi, Zifan Xu, Bo Liu +2
Multi-task Reinforcement Learning (MTRL) has emerged as a critical training paradigm for applying reinforcement learning (RL) to a set of complex real-world robotic tasks, which de…
Learning Memory Mechanisms for Decision Making through Demonstrations
William Yue, Bo Liu, Peter Stone
In Partially Observable Markov Decision Processes, integrating an agent's history into memory poses a significant challenge for decision-making. Traditional imitation learning, rel…
Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting
Bo Liu, Mao Ye, Peter Stone +1
A fundamental challenge in continual learning is to balance the trade-off between learning new tasks and remembering the previously acquired knowledge. Gradient Episodic Memory (GE…