NeurIPS
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
Download Abstract: Gradient-based Meta-RL (GMRL) refers …
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Multi-Agent Reinforcement Learning is A Sequence Modeling Problem
Download Abstract: Large sequence model (SM) such as GP …
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Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning
Download Abstract: Setting up a well-designed reward fu …
A Unified Diversity Measure for Multiagent Reinforcement Learning
Download Abstract: Promoting behavioural diversity is o …
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Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation
Download Abstract: Learning new task-specific skills fr …
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Constrained Update Projection Approach to Safe Policy Optimization
Download Abstract: Safe reinforcement learning (RL) stu …
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Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning
Download Abstract: Achieving human-level dexterity is a …
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MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control
Download Abstract: We introduce the Multi-Agent Trackin …
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TarGF: Learning Target Gradient Field for Object Rearrangement
Download Abstract: Object Rearrangement is to move obje …
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