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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Reinforcement Learning in Robotics
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

1,145 results · 1 filter active ·
Categories
Machine labels · sparse coverage
Evidence
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,145 works in the cohort · of 4,299,418page 1 of 23

Labels cover 2 of 1,145 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 1,145 of 1,145 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundunlabeled
Deep Reinforcement Learning That Matters
2018· article· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · noneconsensus · none
1,504
citations
afffundunlabeled
The Option-Critic Architecture
2017· article· en· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
695
citations
affno abstractunlabeled
Natural actor–critic algorithms
2009· article· en· Automatica· Computer Science
distilled prediction:candidate · noneconsensus · none
569
citations
afffundunlabeled
Online Planning Algorithms for POMDPs
2008· article· en· Journal of Artificial Intelligence Research· Computer Science
distilled prediction:candidate · noneconsensus · none
515
citations
affno abstractunlabeled
A survey of point-based POMDP solvers
2012· article· en· Autonomous Agents and Multi-Agent Systems· Computer Science
distilled prediction:candidate · noneconsensus · none
433
citations
affno abstractunlabeled
Learning Options in Reinforcement Learning
2002· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrow+research_integrityconsensus · none
270
citations
affunlabeled
Model-Based Bayesian Exploration
2013· article· en· arXiv (Cornell University)· Computer Science
distilled prediction:candidate · noneconsensus · none
235
citations
affunlabeled
Bayesian Reinforcement Learning: A Survey
2015· article· en· Foundations and Trends® in Machine Learning· Computer Science
distilled prediction:candidate · noneconsensus · none
223
citations
afffundunlabeled
The Option-Critic Architecture
2017· preprint· en· Proceedings of the AAAI Conference on Artificial Intelligence· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_scienceconsensus · none
209
citations
affunlabeled
Opposition-Based Reinforcement Learning
2006· article· en· Journal of Advanced Computational Intelligence and Intelligent Informatics· Computer Science
distilled prediction:candidate · noneconsensus · none
207
citations
affunlabeled
Bayes-Adaptive POMDPs
2007· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
112
citations
affunlabeled
Regularized Policy Iteration
2008· article· en· PolyPublie (École Polytechnique de Montréal)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
108
citations
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