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Research map / Reinforcement learning / Visual and representation RL

RL with tree search for discovery

Search molecules and plans with RL and Monte Carlo tree search.

121 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026) · an approach in Visual and representation RL, keyword cluster “search · decision · systems”

State History Tried Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

41 papers in 2023–24 and 35 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 7.2% to 5.0%.

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 4162017: 2172018: 5182019: 2192020: 13202021: 9212022: 10222023: 24232024: 17242025: 17252026: 1826

Most cited paper of each year

Earliest papers here

What has been tried

97 papers here report 900 measured changes (a component added, removed or swapped, compared with a baseline): helped 68%, no clear effect 10%, hurt 18%, mixed 4%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
add optimal value supervisorGALA · Converged reward sum-0.01 -> 4.43HelpedEarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading (AAAI 2024 · 21 citations)
Replace a GRU-based DQN agent with a GRU-based PPO agent9 victim websites · TFA224 -> 197HelpedBertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer (Student Abstract) (AAAI 2024 · 7 citations)
add the leader's incentiveEDRP · ORR0.76±0.00 -> 0.79±0.02HelpedTransition-Informed Reinforcement Learning for Large-Scale Stackelberg Mean-Field Games (AAAI 2024 · 7 citations)
Add prefix-enhanced training with prefix-to-full samplesMuST-C En-De tst-COMMON · BLEU>2 BLEU points around the 1000ms markHelpedDivergence-Guided Simultaneous Speech Translation (AAAI 2024 · 6 citations)
Use local and global sequence features in LGFEN rather than an MLP predictorDNA, Top10 mean · mean binding activity0.981 ± 0.008 -> 0.989 ± 0.006HelpedDesigning Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning (AAAI 2024 · 4 citations)
Use SMILES instead of SELFIESPyTDC tasks · rewardHelpedSearching for High-Value Molecules Using Reinforcement Learning and Transformers (ICLR 2024 · 3 citations)
add metadata to GenoARE. coli · accuracy89.57 -> 94.04HelpedOptimizing Gene-Based Testing for Antibiotic Resistance Prediction (AAAI 2025 · 1 citation)
add genetic search to the GFlowNet policy trainingPMO 23 oracles · AUC Top-1015.738 -> 16.213HelpedGenetic-guided GFlowNets for Sample Efficient Molecular Optimization (NeurIPS 2024 · 1 citation)
add visual features to the tabular-only modelSmall-area search, 2.5%, 5%, and 10% positive rates · ANT1.008 -> 1.052; 1.972 -> 2.240; 4.216 -> 4.372HelpedActive Geospatial Search for Efficient Tenant Eviction Outreach (AAAI 2025 · 0 citations)
Use codebook size k=1 instead of k=4CraftWorld Standard test · Expansions103.23 -> 263.92HurtSubgoal-Guided Policy Heuristic Search with Learned Subgoals (ICML 2025 · 0 citations)
Apply contrastive training to question–KC and solution step–KC pairsKC-cluster question retrieval · micro-F10.2305 -> 0.8865HelpedPersonalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing (NeurIPS 2025 · 0 citations)
Add abstraction learning to evolutionary program synthesisarithmetic_base · ground-truth entities per episodic roll-out23.98HelpedLearning Interestingness in Automated Mathematical Theory Formation (NeurIPS 2025 · 0 citations)

What reviewers will expect

Datasets and baselines named in the 23 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Baselines

  • Random · 2 of 23 papers
  • random policy · 2 of 23 papers
  • ReAct · 2 of 23 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 76 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 39 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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