ASSUME Framework
✨An open-source agent-based simulation toolbox for European electricity markets, supporting deep reinforcement learning bidding strategies and grid congestion management modeling.
An open-source agent-based simulation toolbox for European electricity markets, supporting deep reinforcement learning bidding strategies and grid congestion management modeling.
A tutorial project for an AI Love Master app and ReAct autonomous agent built on Spring Boot 3 and Java 21, featuring Spring AI, RAG, Tool Calling, and MCP practices.
A modular Python toolkit developed by the University of Innsbruck that integrates information retrieval, re-ranking, and RAG generation, featuring 40+ pre-processed datasets and single-line pipeline construction.
A systematic skill library for AI Agent context management, covering fundamentals, architectural patterns, operational optimization, and evaluation systems. Compatible with Claude Code, Cursor, and other platforms. Distinguished from prompt engineering by its holistic approach to curating all information entering the model's attention budget.
An AI-driven multi-agent research assistant based on LangGraph that automates the entire research workflow from hypothesis generation, data analysis, and visualization to comprehensive report writing.
A generative agent framework inspired by human dual-process theory, combining fast and slow thinking mechanisms with in-context reinforcement learning to efficiently solve complex interactive reasoning tasks.
An agentic graph language assistant framework developed by HKUDS, based on Llama3-8B, unifying predictive tasks (e.g., node classification) and generative tasks (e.g., text summarization) on graph data through collaborative agents for generation, planning, and execution.
Odyssey is a framework that empowers LLM-based Minecraft agents with open-world skills, featuring 40 primitive skills and 183 compositional skills, enabling AI to autonomously explore, learn, and execute diverse tasks in the Minecraft universe.
A symbiotic AI agent that remembers everything, challenges you, and extends your cognition. Not just a chatbot, but an intelligent partner that works alongside you in your system.
Science-Star is an open platform for building, extending, and experimenting with scientific AI agents. It features a ReAct-based engine with integrated planning, action, memory and reflection modules, visualization tools, and a modular architecture for easy customization.
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