85 citations · 128 across the 10 of their papers we have counts for
10 papers
Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents
Arrasy Rahman, Jiaxun Cui, Peter Stone
Robustly cooperating with unseen agents and human partners presents significant challenges due to the diverse cooperative conventions these partners may adopt. Existing Ad Hoc Team…
Composing Efficient, Robust Tests for Policy Selection
Dustin Morrill, Thomas J. Walsh, Daniel Hernandez +2
Modern reinforcement learning systems produce many high-quality policies throughout the learning process. However, to choose which policy to actually deploy in the real world, they…
FAMO: Fast Adaptive Multitask Optimization
Bo Liu, Yihao Feng, Peter Stone +1
One of the grand enduring goals of AI is to create generalist agents that can learn multiple different tasks from diverse data via multitask learning (MTL). However, in practice, a…
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
Bo Liu, Yifeng Zhu, Chongkai Gao +4
Lifelong learning offers a promising paradigm of building a generalist agent that learns and adapts over its lifespan. Unlike traditional lifelong learning problems in image and te…
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang +4
Large language models (LLMs) have demonstrated remarkable zero-shot generalization abilities: state-of-the-art chatbots can provide plausible answers to many common questions that…
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
Event Tables for Efficient Experience Replay
Varun Kompella, Thomas J. Walsh, Samuel Barrett +2
Experience replay (ER) is a crucial component of many deep reinforcement learning (RL) systems. However, uniform sampling from an ER buffer can lead to slow convergence and unstabl…
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach
Mao Ye, Bo Liu, Stephen Wright +2
Bilevel optimization (BO) is useful for solving a variety of important machine learning problems including but not limited to hyperparameter optimization, meta-learning, continual…
Effective Mutation Rate Adaptation through Group Elite Selection
Akarsh Kumar, Bo Liu, Risto Miikkulainen +1
Evolutionary algorithms are sensitive to the mutation rate (MR); no single value of this parameter works well across domains. Self-adaptive MR approaches have been proposed but the…
A Survey of Ad Hoc Teamwork Research
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman +5
Ad hoc teamwork is the research problem of designing agents that can collaborate with new teammates without prior coordination. This survey makes a two-fold contribution: First, it…