REPOGEO REPORT · LITE
opendilab/awesome-model-based-RL
Default branch main · commit ddc42b0d · scanned 5/9/2026, 4:08:17 PM
GitHub: 1,346 stars · 77 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface opendilab/awesome-model-based-RL, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README's opening statement to clarify its role as a curated directory
Why:
CURRENTThis is a collection of research papers for **model-based reinforcement learning (mbrl)**.
COPY-PASTE FIXThis is the definitive curated list and comprehensive directory of research papers, code, and resources for **model-based reinforcement learning (MBRL)**, designed to help researchers and practitioners navigate the field.
- mediumabout#2Add repository URL to the 'Homepage' field in About section
Why:
COPY-PASTE FIXhttps://github.com/opendilab/awesome-model-based-RL
- lowtopics#3Add 'research-papers' topic
Why:
CURRENTawesome, awesome-list, model-based-reinforcement-learning, model-based-rl, reinforcement-learning, reinforcement-learning-algorithms
COPY-PASTE FIXawesome, awesome-list, model-based-reinforcement-learning, model-based-rl, reinforcement-learning, reinforcement-learning-algorithms, research-papers
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- DeepMind · recommended 2×
- arXiv.org · recommended 2×
- Reinforcement Learning: An Introduction" by Sutton and Barto · recommended 1×
- DreamerV3 · recommended 1×
- MuZero · recommended 1×
- CATEGORY QUERYWhere can I find a comprehensive collection of resources for model-based reinforcement learning?you: not recommendedAI recommended (in order):
- Reinforcement Learning: An Introduction" by Sutton and Barto
- DeepMind
- DreamerV3
- MuZero
- AlphaZero
- Model-Based Reinforcement Learning: A Survey" by Mo Chen et al.
- OpenAI Spinning Up in Deep RL
- PyTorch
- TensorFlow
- Stable Baselines3
- Tianshou
- Dreamer
- PlaNet
- Stanford
- UC Berkeley
- Carnegie Mellon
- arXiv.org
AI recommended 17 alternatives but never named opendilab/awesome-model-based-RL. This is the gap to close.
Show full AI answer
- CATEGORY QUERYHow can I stay updated on the latest research papers in model-based reinforcement learning?you: not recommendedAI recommended (in order):
- arXiv Sanity Preserver
- arXiv.org
- Google Scholar
- DeepMind
- Meta AI
- Google AI
- OpenAI
- NeurIPS
- ICML
- ICLR
- AAAI
- IJCAI
- CoRL
- OpenReview
- PMLR
- DeepMind Blog
- OpenAI Blog
- The Batch
- DeepLearning.AI
- Import AI
- ConnectedPapers
- Semantic Scholar
AI recommended 23 alternatives but never named opendilab/awesome-model-based-RL. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of opendilab/awesome-model-based-RL?passAI did not name opendilab/awesome-model-based-RL — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts opendilab/awesome-model-based-RL in production, what risks or prerequisites should they evaluate first?passAI named opendilab/awesome-model-based-RL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo opendilab/awesome-model-based-RL solve, and who is the primary audience?passAI did not name opendilab/awesome-model-based-RL — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of opendilab/awesome-model-based-RL. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/opendilab/awesome-model-based-RL)<a href="https://repogeo.com/en/r/opendilab/awesome-model-based-RL"><img src="https://repogeo.com/badge/opendilab/awesome-model-based-RL.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
opendilab/awesome-model-based-RL — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite