AgentDB Learning Plugins
CommunityTrain AI agents with 9 RL algorithms, learn from experience.
Software Engineering#machine learning#ai agents#agentdb#reinforcement learning#q-learning#decision transformer#actor-critic#learning plugins
AuthorRyanJarv
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Implementing reinforcement learning (RL) algorithms for AI agents is complex and requires specialized knowledge. This Skill provides AgentDB's plugin system, offering 9 pre-built RL algorithms (e.g., Decision Transformer, Q-Learning, Actor-Critic) to create, train, and deploy self-learning agents. It simplifies the process of optimizing agent behavior through experience, even for complex tasks.
Core Features & Use Cases
- 9 Reinforcement Learning Algorithms: Access a suite of RL algorithms for various learning scenarios, including offline and online methods.
- WASM-Accelerated Training: Train models 10-100x faster with optimized neural inference.
- Use Case: Develop a game-playing agent by creating a Decision Transformer plugin, collecting game experiences (state, action, reward), and then training the model to learn optimal strategies from historical data without direct environment interaction.
Quick Start
Use the AgentDB Learning Plugins skill to create a new learning plugin using the 'decision-transformer' template, naming it 'my-agent'.
Dependency Matrix
Required Modules
nodeagentic-flowagentdb
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: AgentDB Learning Plugins Download link: https://github.com/RyanJarv/dockerfiles/archive/main.zip#agentdb-learning-plugins Please download this .zip file, extract it, and install it in the .claude/skills/ directory.