on-policy
★ 2.1k
vs
OGAM
★ 3.1k
on-policy vs OGAM
on-policy: This repository implements MAPPO, a multi-agent variant of PPO, widely used in cooperative multi-agent games and research. It provides robust implementations for various multi-agent environments like StarCraft II, Hanabi, and Google Research Football, along with detailed training scripts and hyperparameter guidance.; OGAM: Off Grid AI is a comprehensive offline AI suite that brings advanced capabilities like text and image generation, vision AI, and voice input directly to your phone or Mac. It ensures complete data privacy by running all AI operations on-device, without sending any data to the cloud.
01
TL;DR
Choose on-policy if…Research and experimentation in cooperative multi-agent reinforcement learning
Choose OGAM if…Use as a private, offline AI assistant for chatting and brainstorming.
02
Side-by-Side Comparison
03
Features
on-policy01Implementation of MAPPO (Multi-Agent PPO)
02Support for diverse multi-agent environments (e.g., StarCraft II, Hanabi)
03Ready-to-use training scripts for various scenarios
04Detailed hyperparameter guidance and updated results
05Default support for shared policy among agents
OGAM01On-device Text Generation with various LLMs
02Local Stable Diffusion for Image Generation
03Camera-based Vision AI for scene and document analysis
04Function calling with built-in tools (web search, calculator, knowledge base)
05On-device RAG for document analysis and knowledge retrieval
04
Use Cases
on-policy↳Research and experimentation in cooperative multi-agent reinforcement learning
↳Benchmarking and evaluating PPO's effectiveness in MARL scenarios
↳Training AI agents for popular multi-agent games like StarCraft II and Hanabi
OGAM↳Use as a private, offline AI assistant for chatting and brainstorming.
↳Generate images and text for creative projects without cloud dependency.
↳Analyze local documents (PDFs, text files) and ask questions using the knowledge base.
↳Interact hands-free with the AI using on-device voice input and text-to-speech (Pro feature).
↳Perform AI tasks locally, ensuring zero data leaves your device for privacy-sensitive applications.
05
Best For
on-policyTrendingReinforcement LearningMulti-Agent AI
OGAMTrending
FAQ
FAQ
What is the difference between on-policy and OGAM?
Both on-policy and OGAM are in the LLM Infra category. on-policy has 2.1k stars, while OGAM has 3.1k stars.
Which is better, on-policy or OGAM?
The best choice depends on your use case. Choose on-policy if Research and experimentation in cooperative multi-agent reinforcement learning, and OGAM if Use as a private, offline AI assistant for chatting and brainstorming..
Is on-policy free or open source?
Yes, on-policy is open source on GitHub (MIT).
Is OGAM free or open source?
Yes, OGAM is open source on GitHub (MIT).
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