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Research map / Reinforcement learning / Visual and representation RL

General Policies, Representations, and Planning Width

AAAI 2021 · Reinforcement learning › Visual and representation RL · approach: RL with tree search for discovery · 17 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add the rule {¬H} → {H, p?, t?} (ablation)Delivery sketches · Delivery-1 (QD1)sketch width: 2 -> 1Helped
Add the rule {¬H} → {H, p?, t?} (ablation)Delivery sketches · Delivery (QD)sketch widthNo clear effect
Add the rule {n > 0} → {n↓, H?, p?, t?} (ablation)Delivery sketches · Delivery (QD)sketch width: unb -> 2Helped
Combine the rules in σ2 and σ4 (ablation)Delivery sketches · Delivery (QD)sketch width: 2 -> 1Helped
Add the rule {¬H, p > 0} → {p↓, t?} (ablation)Delivery sketches · Delivery-1 (QD1)sketch width: 2No clear effect
Add the rule {¬H, p > 0} → {p↓, t?} (ablation)Delivery sketches · Delivery (QD)sketch widthNo clear effect
Add the rule {H, t > 0} → {t↓, p?} (ablation)Delivery sketches · Delivery-1 (QD1)sketch width: 2No clear effect
Add the rule {H, t > 0} → {t↓, p?} (ablation)Delivery sketches · Delivery (QD)sketch widthNo clear effect
Combine the rules in σ2, σ4, σ6, and σ7 (ablation)Delivery sketches · Delivery-1 (QD1)sketch width: 1 -> 0Helped
Combine the rules in σ2, σ4, σ6, and σ7 (ablation)Delivery sketches · Delivery (QD)sketch width: 1 -> 0Helped

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