@inproceedings{89df67e391414c75b861baae7fa8402c,
title = "Conscious knowledge based question answering",
abstract = "A model of consciousness proposed by neuroscientists in 1989 is called the theater model, which uses theater as an analogy to describe {"}what is consciousness{"}. This paper simplifies the problem of question answering and uses theater model to simulate the question answering mechanism of the human brain. We extract a small amount of knowledge from Freebase and use it as agents' knowledge base. Then we build a multi-round question answering agent based on the theater model and Deep Q-learning. We train the two agents against each other, and finally analyze the training results. The results show that the question answering mechanism and training method designed can simulate the human dialogue scene well, and agents have different behavior when setting different rewarding parameters.",
keywords = "Conscious machine, Question answering, Reinforcement learning, Theater model of consciousness",
author = "Shirong Liu and Zixian Guo and Hongzhi Wang",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 2020 ACM Turing Celebration Conference - China, ACM TURC 2020 ; Conference date: 21-05-2021 Through 23-05-2021",
year = "2020",
month = may,
day = "22",
doi = "10.1145/3393527.3393552",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "145--149",
booktitle = "ACM TURC 2020 - Proceedings of ACM Turing Celebration Conference - China",
address = "美国",
}