RRepoGEO

REPOGEO REPORT · LITE

shariqiqbal2810/maddpg-pytorch

Default branch master · commit 40388d7c · scanned 6/1/2026, 2:23:17 AM

GitHub: 690 stars · 135 forks

AI VISIBILITY SCORE
22 /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
1 / 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 shariqiqbal2810/maddpg-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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    multi-agent-reinforcement-learning, maddpg, pytorch, deep-reinforcement-learning, actor-critic, multi-agent-systems, machine-learning, research-code
  • mediumreadme#2
    Refine README's opening statement to emphasize its role as a direct implementation

    Why:

    CURRENT
    PyTorch Implementation of MADDPG from *Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments* (Lowe et. al. 2017)
    COPY-PASTE FIX
    This repository provides a faithful and standalone PyTorch implementation of the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, as described in *Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments* (Lowe et. al. 2017).
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add the URL to the original MADDPG paper (Lowe et. al. 2017) or a dedicated project page if one exists.

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 shariqiqbal2810/maddpg-pytorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RLlib
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RLlib · recommended 1×
  2. PettingZoo · recommended 1×
  3. OpenSpiel · recommended 1×
  4. MARL-Baselines · recommended 1×
  5. Stable Baselines3 · recommended 1×
  • CATEGORY QUERY
    How to implement multi-agent deep reinforcement learning for cooperative-competitive scenarios?
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. PettingZoo
    3. OpenSpiel
    4. MARL-Baselines
    5. Stable Baselines3

    AI recommended 5 alternatives but never named shariqiqbal2810/maddpg-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch implementation for multi-agent actor-critic algorithms in mixed environments.
    you: not recommended
    AI recommended (in order):
    1. MARL-Algorithms (Pytorch-RL-V2/MARL-Algorithms)
    2. PyMARL (oxwhirl/pymarl)
    3. RLlib (ray-project/ray)
    4. OpenSpiel (deepmind/open_spiel)
    5. MAAC
    6. SMAC Baselines (oxwhirl/smac)

    AI recommended 6 alternatives but never named shariqiqbal2810/maddpg-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 shariqiqbal2810/maddpg-pytorch?
    pass
    AI did not name shariqiqbal2810/maddpg-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 shariqiqbal2810/maddpg-pytorch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named shariqiqbal2810/maddpg-pytorch 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 shariqiqbal2810/maddpg-pytorch solve, and who is the primary audience?
    pass
    AI did not name shariqiqbal2810/maddpg-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?

Embed your GEO score

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shariqiqbal2810/maddpg-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
shariqiqbal2810/maddpg-pytorch — RepoGEO report