Jingyi Huang

Exploration and Exploitation: A Study on Sample Efficiency in Reinforcement Learning With Multifaceted Curiosity Rewards and Adaptive Experience Replay Utilisation in Sparse Reward Environments

2026 · CAAI Transactions on Intelligence Technology

ABSTRACT In recent years, the widespread application of deep reinforcement learning (DRL) in autonomous systems has highlighted the importance of achieving high sample efficiency under sparse reward conditions. To improve sample efficiency in sparse reward …