Reinforcement Learning with Deep Learning

深度学习强化学习

• 批准号: 1928590
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1928590
• 关键词: Reinforcement; Learning; Deep

Advances in RL using deep learning have led to solutions for more complex tasks. There is, however, a need for relatively large amounts of training data. One method to address this issue is to leverage data from different tasks using multi-task learning approaches. The project will take forward this approach to see if this will enable more sample efficient learning and importantly transfer of experience gained on earlier tasks to novel tasks.

使用深度学习的RL的进步已经为更复杂的任务带来了解决方案。然而，需要相对大量的训练数据。解决这个问题的一种方法是使用多任务学习方法来利用来自不同任务的数据。该项目将采用这种方法，看看这是否能使更多的样本有效的学习和重要的经验转移到新的任务获得早期任务。