RRepoGEO

REPOGEO REPORT · LITE

vietnh1009/Super-mario-bros-PPO-pytorch

Default branch master · commit ab4248d7 · scanned 5/22/2026, 12:33:03 PM

GitHub: 1,287 stars · 239 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
15 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
0 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 vietnh1009/Super-mario-bros-PPO-pytorch, 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.

OVERALL DIRECTION
  • highreadme#1
    Reposition README introduction to highlight 'example' nature

    Why:

    CURRENT
    Here is my python source code for training an agent to play super mario bros. By using Proximal Policy Optimization (PPO) algorithm introduced in the paper **Proximal Policy Optimization Algorithms** paper.
    COPY-PASTE FIX
    This repository provides a complete, runnable PyTorch example for training an AI agent to play Super Mario Bros using the Proximal Policy Optimization (PPO) algorithm, as introduced in the paper **Proximal Policy Optimization Algorithms**.
  • mediumhomepage#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/vietnh1009/Super-mario-bros-PPO-pytorch
  • lowtopics#3
    Add more specific topics to emphasize application and game AI

    Why:

    CURRENT
    ai, deep-learning, gym, mario, openai, openai-gym, ppo, ppo2, proximal-policy-optimization, python, python3, pytorch, reinforcement-learning, super-mario-bros
    COPY-PASTE FIX
    ai, deep-learning, gym, mario, openai, openai-gym, ppo, ppo2, proximal-policy-optimization, python, python3, pytorch, reinforcement-learning, super-mario-bros, rl-example, game-ai, retro-gaming

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.

Recall
0 / 2
0% of queries surface vietnh1009/Super-mario-bros-PPO-pytorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DLR-RM/stable-baselines3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DLR-RM/stable-baselines3 · recommended 1×
  2. laskain/pytorch-drl · recommended 1×
  3. vwxyzjn/cleanrl · recommended 1×
  4. ray-project/ray · recommended 1×
  5. Farama-Foundation/Minigrid · recommended 1×
  • CATEGORY QUERY
    What are good PyTorch examples for deep reinforcement learning in gaming?
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3 (SB3) (DLR-RM/stable-baselines3)
    2. PyTorch-DRL (by Misha Laskin et al.) (laskain/pytorch-drl)
    3. CleanRL (vwxyzjn/cleanrl)
    4. RLlib (part of Ray) (ray-project/ray)
    5. Minigrid-RL (by Farama Foundation) (Farama-Foundation/Minigrid)

    AI recommended 5 alternatives but never named vietnh1009/Super-mario-bros-PPO-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to apply PPO algorithm to build AI agents for retro platformer games?
    you: not recommended
    AI recommended (in order):
    1. Gymnasium
    2. gym-retro
    3. Stable Baselines3
    4. PyTorch
    5. TensorFlow
    6. Optuna
    7. Weights & Biases
    8. Ray Tune
    9. OpenCV
    10. Pillow

    AI recommended 10 alternatives but never named vietnh1009/Super-mario-bros-PPO-pytorch. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

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 vietnh1009/Super-mario-bros-PPO-pytorch?
    pass
    AI did not name vietnh1009/Super-mario-bros-PPO-pytorch — 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 vietnh1009/Super-mario-bros-PPO-pytorch in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name vietnh1009/Super-mario-bros-PPO-pytorch — 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?

  • In one sentence, what problem does the repo vietnh1009/Super-mario-bros-PPO-pytorch solve, and who is the primary audience?
    pass
    AI did not name vietnh1009/Super-mario-bros-PPO-pytorch — 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?

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vietnh1009/Super-mario-bros-PPO-pytorch — 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