AgentDB Learning Plugins
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.
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AgentDB Learning Plugins
What This Skill Does
Provides access to 9 reinforcement learning algorithms via AgentDB's plugin system. Create, train, and deploy learning plugins for autonomous agents that improve through experience. Includes offline RL (Decision Transformer), value-based learning (Q-Learning), policy gradients (Actor-Critic), and advanced techniques.
Performance: Train models 10-100x faster with WASM-accelerated neural inference.
Prerequisites
- Node.js 18+
- AgentDB v1.0.7+ (via agentic-flow)
- Basic understanding of reinforcement learning (recommended)
Quick Start with CLI
Create Learning Plugin
# Interactive wizard
npx agentdb@latest create-plugin
# Use specific template
npx agentdb@latest create-plugin -t decision-transformer -n my-agent
# Preview without creating
npx agentdb@latest create-plugin -t q-learning --dry-run
# Custom output directory
npx agentdb@latest create-plugin -t actor-critic -o ./plugins
List Available Templates
# Show all plugin templates
npx agentdb@latest list-templates
# Available templates:
# - decision-transformer (sequence modeling RL - recommended)
# - q-learning (value-based learning)
# - sarsa (on-policy TD learning)
# - actor-critic (policy gradient with baseline)
# - curiosity-driven (exploration-based)
Manage Plugins
# List installed plugins
npx agentdb@latest list-plugins
# Get plugin information
npx agentdb@latest plugin-info my-agent
# Shows: algorithm, configuration, training status