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作 者:李春文[1] 陆思聪[1] 吴热冰[1] 丁青青[2] 刘华平[3] 李东海[4] 张靖[1] 薛拾贝 徐长波 于轩 徐海峰 张之梦 许舒翔 祝乐 李颜初 韩蓝天 崔雨 LI Chun wen;LU Si-cong;WU Re bing;DING Qing-qing;LIU Hua-ping;LI Dong-hai;ZHANG Jing;XUE Shi-bei;XU Chang-bo;YU Xuan;XU Hai-feng;ZHANG Zhi-meng;XU Shur xiang;ZHU Le;LI Yan-chu;HAN Lan-tian;CUI Yu(Department of Automation.Tsinghua University,Beijing 100084;Department of Electrical Engineering,Tsinghua University,Beijing 100084;Department of Computer Science and Technology,Tsinghua University,Beijing 100084;Depariment of Energy and Power Engineering,Tsinghua University.Beijing 100084;Depariment of Automation,Shanghai Jiao Tong Universily,Shanghai 200240;School of Information Engineering,Beijing Insiute of Graphic Communicarion,Beijing 102600;School of Information and Conmunication Engineering.Beijing Universiy of Posts and Telecommurications,Beiing,100876)
机构地区:[1]清华大学自动化系,北京100084 [2]清华大学电机工程与应用电子技术系,北京100084 [3]清华大学计算机科学与技术系,北京100084 [4]清华大学能源与动力工程系,北京100084 [5]上海交通大学自动化系,上海200240 [6]北京印刷学院信息工程学院,北京102600 [7]北京邮电大学信息与通信工程学院,北京100876
出 处:《清华大学教育研究》2022年第3期25-32,共8页Tsinghua Journal of Education
基 金:国家自然科学基金面上项目“网络化多运动体智能协同系统动力学建模、控制与调度”(61174068)。
摘 要:沿着人工智能从起源到应用的演化脉络,本文分析研究了其学科发展路径上的一些关键问题。首先,对人工智能领域的产生到专家系统的这一发展阶段进行了历史回顾和定位分析,概括了当前人工智能在理论方法和应用展开方面的基本领域分支及其分布状态。进一步,从拟人与超人这一话题切入,探讨了人机会话中智能的判别标准及对未来发展的预期。然后,分析了当前深度学习方法的自主与内蕴特性,并从不同角度分析了自然语言处理领域中智能会话面临的困难,探索其以人格与情感为代表的产生根源和可能的解决方向,并特别论述了普适人工智能与教育发展的特殊联系。From the origin to the application of artificial intelligence, some key problems along with the development of this discipline are analyzed. Firstly, a historical review and evaluation are carried out to the development stage from the birth of the artificial intelligence field to the expert system, following which we summarize the fundamental branches and their distribution in the theory and application of artificial intelligence. Further, induced from the topic of anthropomorphic and superman, the discriminative criteria of intelligence in human-machine conversation and the expectation of future development are discussed. Then the autonomous and intrinsic characteristics of the current deep learning methods are analyzed. Furthermore, from different angles, the difficulties faced by intelligent conversations in the field of natural language processing are analyzed, and the causes(typically by the personality and emotion) and possible solutions are discussed. Then the special relationship between general artificial intelligence and the development of education is mentioned.
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