A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access

Computer Science

• Reinforcement Learning 100%
• Learning Framework 100%
• Deep Reinforcement Learning 100%
• multi agent 50%
• Channel Condition 50%
• Agent Framework 50%
• Access Channel 50%
• Channel Access 50%
• Random Access 50%
• Time Efficiency 50%
• Deep Q-Network 50%

Keyphrases

• Collision Probability 33%
• Channel Access Method 33%
• Decentralized Multi-Agent 33%
• Learning Policy 33%

Engineering

• Decentralized Multi 25%
• User Model 25%