论文标题
机器人智能的深层因果学习
Deep Causal Learning for Robotic Intelligence
论文作者
论文摘要
该邀请的评论在机器人智能的背景下讨论了因果学习。该论文介绍了有关人类认知因果学习的心理发现，然后引入了有关因果发现和因果推论的传统统计解决方案。该论文回顾了最近的深层因果学习算法，重点是它们的架构以及使用深网的好处，并讨论了深层因果学习与机器人智能需求之间的差距。
This invited review discusses causal learning in the context of robotic intelligence. The paper introduced the psychological findings on causal learning in human cognition, then it introduced the traditional statistical solutions on causal discovery and causal inference. The paper reviewed recent deep causal learning algorithms with a focus on their architectures and the benefits of using deep nets and discussed the gap between deep causal learning and the needs of robotic intelligence.
