AgentDB Reinforcement Learning

The AgentDB Learning Plugins skill empowers developers to build self-improving agents using a suite of nine reinforcement learning algorithms, including Decision Transformers, Actor-Critic, and Q-Learning. By leveraging WASM-accelerated neural inference, it provides 10-100x faster training and execution directly within the agent workflow. This skill is essential for implementing offline RL from historical logs, online learning through environment interaction, and advanced techniques like curriculum or multi-task learning to enhance agent decision-making over time.

Key Features

Use Cases