4   Artículos

 
en línea
Charl Maree and Christian Omlin    
The increased complexity of state-of-the-art reinforcement learning (RL) algorithms has resulted in an opacity that inhibits explainability and understanding. This has led to the development of several post hoc explainability methods that aim to extract ... ver más
Revista: AI    Formato: Electrónico

 
en línea
Hongjie Zhang, Cheng Qu, Jindou Zhang and Jing Li    
Deep Reinforcement Learning (DRL) is a promising approach for general artificial intelligence. However, most DRL methods suffer from the problem of data inefficiency. To alleviate this problem, DeepMind proposed Prioritized Experience Replay (PER). Thoug... ver más
Revista: Applied Sciences    Formato: Electrónico

« Anterior     Página: 1 de 1     Siguiente »