Project 1 - Efficient Transmission in Deep Reinforcement Learning

Individual Research Project:

1. Compared the impact of packet loss (latency) and noise (reliability) on the transmission between DRL agent and environment, and demonstrated that latency is more crucial for the overall DRL accuracy

2. Addressed the problem that some observation channels are more critical than others by proving that an importance-based resource allocation scheme is needed for a DRL agent

3. Proposed an Efficient Transmission Scheme for DRL agents to identify the essential observation channels when making a decision, and proposed further research to adapt this scheme to a time-varying hostile channel condition