14 citations · 14 across the 6 of their papers we have counts for
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cs.LG2024
Robust Guided Diffusion for Offline Black-Box Optimization
Can Sam Chen, Christopher Beckham, Zixuan Liu +2
Offline black-box optimization aims to maximize a black-box function using an offline dataset of designs and their measured properties. Two main approaches have emerged: the forwar…
cs.LG2019★ 14 cited
Real-Time Reinforcement Learning
Simon Ramstedt, Christopher Pal
Markov Decision Processes (MDPs), the mathematical framework underlying most algorithms in Reinforcement Learning (RL), are often used in a way that wrongfully assumes that the sta…
cs.LG2019
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
Julien Roy, Paul Barde, Félix G. Harvey +2
In multi-agent reinforcement learning, discovering successful collective behaviors is challenging as it requires exploring a joint action space that grows exponentially with the nu…