Search Results for "e-learning"
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Showing 9 open source projects for "e-learning"
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AgentUniverse
agentUniverse is a LLM multi-agent framework
AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation. -
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VectorizedMultiAgentSimulator (VMAS)
VMAS is a vectorized differentiable simulator
VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently. -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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OpenAI Swarm
Educational framework exploring multi-agent orchestration
...These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning curve. Approaches similar to Swarm are best suited for situations dealing with a large number of independent capabilities and instructions. Swarm runs (almost) entirely on the client and, much like the Chat Completions API, does not store state between calls. -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
7
OWL
Optimized Workforce Learning for General Multi-Agent Assistance
Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. OWL (Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation) is an advanced framework designed to enhance multi-agent collaboration, improving task automation across various domains. By utilizing dynamic agent interactions, OWL aims to streamline and optimize complex workflows, making AI collaboration more natural, efficient, and adaptable. ... -
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Zeta
Build high-performance AI models with modular building blocks
zeta is a deep learning library focused on providing cutting-edge AI and neural network models with a strong emphasis on research-grade architectures. It includes state-of-the-art implementations for rapid experimentation and model building. -
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XAgent
An Autonomous LLM Agent for Complex Task Solving
XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications. -
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