机器推理的进展与展望

The development of machine learning algorithms are limited by the problems, such as weak generalization ability, poor robustness and lack of interpretability. In this paper, the important role of reasoning for machine learning human knowledge and logic, understanding and interpreting the world is illustrated. Firstly, the reasoning mechanism of the human brain is studied from cognitive maps, neurons and reward circuits, to brain-inspired intuitive reasoning, neural networks and reinforcement learning. Then, the current situation, progress and challenges of machine reasoning methods and their interrelationships are summarized, including intuitive reasoning, commonsense reasoning, causal reasoning and relational reasoning. Finally, the application prospects and future research directions of machine reasoning are analyzed.