Data & Research · GitHub ·63 ★

MAPF-GPT-DDG

[IROS-2025] MAPF-GPT-DDG is a scalable decentralized multi-agent pathfinding (MAPF) solver based on imitation learning. It builds upon MAPF-GPT by introducing a novel fine-tuning method called Delta Data Generation (DDG) — a reward-free active learning approach that identifies and corrects failure c

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Details

Author
Cognitive-AI-Systems
Category
Data & Research
Platform
GitHub
Framework
custom
Language
python
Stars
63
First indexed
2026-05-15
Last active
2026-02-21
Directory sync
2026-05-15
@Cognitive-AI-Systems

Overview

[IROS-2025] MAPF-GPT-DDG is a scalable decentralized multi-agent pathfinding (MAPF) solver based on imitation learning. It builds upon MAPF-GPT by introducing a novel fine-tuning method called Delta Data Generation (DDG) — a reward-free active learning approach that identifies and corrects failure c

Quick start

git

git clone https://github.com/Cognitive-AI-Systems/MAPF-GPT-DDG

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What MAPF-GPT-DDG can do

fine-tundata
  • Fine Tun — fine-tun task automation.
  • Data — Reads, transforms, and analyses structured data.

Frequently asked questions

What is MAPF-GPT-DDG?
[IROS-2025] MAPF-GPT-DDG is a scalable decentralized multi-agent pathfinding (MAPF) solver based on imitation learning. It builds upon MAPF-GPT by introducing a novel fine-tuning method called Delta Data Generation (DDG) — a reward-free active learning approach that identifies and corrects failure c
How do I install MAPF-GPT-DDG?
Use git: `git clone https://github.com/Cognitive-AI-Systems/MAPF-GPT-DDG`. Full setup details on the source page linked above.
Is MAPF-GPT-DDG open source?
MAPF-GPT-DDG is published on GitHub.
What are alternatives to MAPF-GPT-DDG?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for MAPF-GPT-DDG is sourced from GitHub, published by Cognitive-AI-Systems.

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