AI was born symbolic and logic. The pioneers of AI have formalized many elegant theories, hypotheses, and applications, such as PSSH and expert systems. From the 1980s, the pendulum swung toward connectionist, a paradigm inspired by the neural connections in brains. With the growing amount of accessible data and ever stronger computing power, connectionist models gain considerable momentum in recent years. This new approach seems to solve many problems in symbolic AI but raises many new issues at the same time. Which one is better to account for human cognition and more promising for AI? There’s no consensus reached. However, despite their vast difference, people began to explore how to integrate them together. Hybrid systems have been proposed and experimented. Other people see them residing at different levels of one unified hierarchical structure. In recent years, it is increasingly realized that the gap is closing, simply because there’s no gap at all from the beginning. The debate is dying down, opening up new opportunities for future hybrid paradigms.[……]

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