Introduction The lack of commonsense knowledge in artificial intelligence systems has long been one of the main bottlenecks hindering the development of this field. Although great strides have been made in recent years through neural language models and commonsense knowledge graphs, the key component of human intelligence, “conceptualization,” has ...

Traditional representation learning methods usually design a fixed basis function architecture to achieve desired properties such as orthogonality and sparsity. In contrast, the idea of deep reinforcement learning is that the designer should not encode the properties of the representation, but instead let the data flow determine the properties of t...