Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
The AgentDB Learning Plugins skill enables developers to create and train AI learning plugins using a suite of nine reinforcement learning algorithms. This skill addresses the need for effective autonomous learning in agents, allowing them to improve their decision-making capabilities based on experience. By leveraging state-of-the-art techniques in reinforcement learning, users can build systems that adapt and optimize their behavior, leading to more efficient and effective solutions in various domains.
The skill includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more.
You need Node.js 18+, AgentDB v1.0.7+, and a basic understanding of reinforcement learning is recommended.
The skill primarily supports offline reinforcement learning techniques, which may not be ideal for real-time training.
You can create a learning plugin using the CLI command 'npx agentdb@latest create-plugin' followed by your desired options.
Yes, you can use the '--dry-run' option to preview the plugin without actually creating it.
Quick Setup:
.claude/skills/Repository
ruvnet/claude-flow