RAN Reinforcement Learning Engineer

What problem does it solve?

This Skill engineers reinforcement learning for RAN systems, enabling multi-objective optimization across energy, mobility, coverage, and capacity using advanced RL techniques and AgentDB integration.

Core Features & Use Cases

• Policy gradients and experience replay for robust learning.
• Multi-objective RL to balance energy, mobility, coverage, and capacity.
• AgentDB integration for faster learning and pattern reuse.

Quick Start

Set up RL workspace and start an RL agent:

• mkdir -p ran-rl/{agents,environments,policies,experience}
• npx agentdb@latest init ./.agentdb/ran-rl.db --dimension 1536
• npm install @tensorflow/tfjs-node gym-js multi-objective-rl