🧠 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
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
🪞 Make your agents recursively self-improve
[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.
Codex plugin that exports local Codex learning signals into Hermes Agent
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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