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Research map / Reinforcement learning / Visual and representation RL

Deep Hierarchical Planning from Pixels

NeurIPS 2022 · Reinforcement learning › Visual and representation RL · approach: Subgoal generation for hierarchical RL · 14 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use hierarchical latent-goal planning with the worker receiving goals from the managerDirector · Egocentric Ant Mazeslearning successHelped
Use hierarchical latent-goal planning with the manager selecting subgoalsDirector · Visual Pin Padstask rewardHelped
Add task reward to the worker in addition to goal rewardDirector · Standard benchmarksperformanceHelped
Add task reward to the worker in addition to goal rewardDirector · 55 Atari gameshuman-normalized median scoreHelped
Use continuous 1024-dimensional world-model goals instead of discrete goal codes (ablation)Director · Sparse-reward environmentsperformanceHurt
Replace max-cosine reward with unnormalized inner-product goal reward (ablation)Director · Goal Reward ablation tasksperformanceNo clear effect
Replace max-cosine reward with InnerNormed goal reward (ablation)Director · Goal Reward ablation tasksperformanceNo clear effect
Replace max-cosine reward with negative Euclidean distance (ablation)Director · Goal Reward ablation tasksperformanceHurt
Apply exploration bonus to the manager to encourage temporally abstract exploration (ablation)Director · Ant Mazelearning successHelped
Add low-level exploration bonus to the worker (ablation)Director · Ant Mazelearning successHurt
Remove the exploration bonus (ablation)Director · Standard benchmarksperformanceNo clear effect

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