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C. Wibault

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#artificial intelligence Preprint Oct 2026

Q-Shaped Options for Hierarchical Reinforcement Learning

Learning to tackle long-horizon, goal-conditioned tasks requires an agent to reason over extended timescales and act across a broad range of states. In principle, Hierarchical Reinforcement Learning (HRL) addresses both challenges through the interaction between action (temporal) and state (spatial) abstraction. First,...

C. Wibault, Antoine Gorceix, Antonio León Villares et al. · 0 citations