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MarcoDava
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AgentDB Learning Plugins

Create and train AI learning plugins with AgentDB reinforcement learning algorithms.

1|Updated Feb 7, 2026
Search Tags:#agentdb#plugins#training#machine-learning#reinforcement-learning#offline-rl#policy-gradient
One-click install
npx skills add https://github.com/MarcoDava/MockCortex --skill agentdb-learning-plugins-marcodava
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: AgentDB Learning Plugins
Source: https://github.com/MarcoDava/MockCortex/tree/main/.agents/skills/agentdb-learning
Command: npx skills add https://github.com/MarcoDava/MockCortex --skill agentdb-learning-plugins-marcodava

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AgentDB Learning Plugins enable developers to quickly create and train AI learning plugins using AgentDB's nine reinforcement learning algorithms, speeding up the deployment of self-learning agents.

Core Features & Use Cases

  • Access to nine RL templates including Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more for building autonomous agents.
  • CLI and API tooling to create, configure, train, and manage plugins across domains.
  • Real-world use cases include automated learning, adaptation to new tasks, and performance optimization in agent-based systems.

Quick Start

Launch the interactive wizard to create a new learning plugin with the AgentDB CLI.

Frequently Asked Questions about AgentDB Learning Plugins

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I train reinforcement learning agents offline?▼

Train reinforcement learning agents offline using the Decision Transformer algorithm included in AgentDB's plugin templates. This allows policy training from historical interaction data without live environment interaction.

Can I use Q-Learning and SARSA for autonomous game agents?▼

Yes, Q-Learning and SARSA value-based methods are available to build autonomous agents for games. These templates help agents learn optimal decision-making policies through environment interaction.

What's the best way to start building an Actor-Critic policy gradient model?▼

Start building an Actor-Critic policy gradient model by launching the interactive wizard via the AgentDB CLI. This guides you through creating and configuring a new learning plugin step by step.

Do I need Node.js to use AgentDB machine learning plugins?▼

Yes, Node.js 18+ and AgentDB v1.0.7+ via agentic-flow are required prerequisites. You also need a basic understanding of reinforcement learning concepts to use the learning plugins.

How many reinforcement learning algorithms are available in AgentDB?▼

AgentDB provides nine reinforcement learning algorithm templates, including Decision Transformer, Q-Learning, SARSA, and Actor-Critic. These cover offline RL, value-based methods, and policy gradients.

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