2024 "sparse-reward tasks" Papers

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Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning

Zeyang Liu, Lipeng Wan, Xinrui Yang et al.

AAAI 2024paperarXiv:2402.17978

PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling

Utsav Singh, Wesley A. Suttle, Brian Sadler et al.

ICML 2024poster

Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree

Lang Feng, Pengjie Gu, Bo An et al.

ICML 2024spotlight