🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai
Search, understand, reproduce, and improve an idea with ease
This repository hosts a customized PPO based agent for Carla. The goal of this project is to make it easier to interact with and experiment in Carla with reinforcement learning based agents -- this, by wrapping Carla in a gym like environment that can handle custom reward functions, custom debug output, etc.
[NAACL 2025] KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
[ACL 2024] AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning
🪞 Make your agents recursively self-improve
A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch
[ACL 2024] Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
Self improving agents through iterations
Beginner-friendly introduction to multi-agent systems, agent interaction, coordination, and core concepts.
Explore AI agent patterns, design principles, and infrastructure to build and deploy practical, user-friendly intelligent agents.
A quick intro to using Unity's MLAgents for MArch'20 students in University College London
A PyTorch re-implementation of World Models (Ha & Schmidhuber, 2018) for CarRacing-v3. The agent solves the track by "dreaming"—using a VAE for perception, an MDN-RNN for memory, and CMA-ES for controller evolution.
个人工作台主页，按独立工作区记录学习、项目、知识库与工具。
Local Codex skills and automations for reusable agent learnings
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