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TD-MPC2: Scalable, Robust World Models for Continuous Control
March 22, 2024, 4:43 a.m. | Nicklas Hansen, Hao Su, Xiaolong Wang
cs.LG updates on arXiv.org arxiv.org
Abstract: TD-MPC is a model-based reinforcement learning (RL) algorithm that performs local trajectory optimization in the latent space of a learned implicit (decoder-free) world model. In this work, we present TD-MPC2: a series of improvements upon the TD-MPC algorithm. We demonstrate that TD-MPC2 improves significantly over baselines across 104 online RL tasks spanning 4 diverse task domains, achieving consistently strong results with a single set of hyperparameters. We further show that agent capabilities increase with model …
arxiv continuous control cs.ai cs.cv cs.lg cs.ro robust scalable type world world models
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