An Interdisciplinary Approach for Teaching Artificial Intelligence to Computer Science Students

Anoop Mishra, Harvey P. Siy
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引用次数: 5

Abstract

Artificial intelligence (AI) is a demanding and important course for computer science education in the universities and open online courses (MOOCs). It includes various introductory and specialized courses for artificial intelligence like knowledge representation, machine learning, reasoning under uncertainty, natural language processing, robotics, and perception of computer vision, etc. We observed that mostly AI courses focus on the Computer Science (CS)-centric approach and lacks core explanation from their roots including philosophy, neuroscience, psychology, cognitive science, linguistics, economics, social science, etc. In this paper, we propose to engage the interdisciplinary approach along with CS-centric approach for teaching AI that includes the disciplines that have been established to tackle the age-old problem of understanding the science of thinking.
计算机科学专业学生人工智能教学的跨学科方法
人工智能(AI)是高校计算机科学教育和网络开放课程(MOOCs)中要求较高的重要课程。它包括各种人工智能的入门和专业课程,如知识表示,机器学习,不确定性推理,自然语言处理,机器人技术和计算机视觉感知等。我们观察到,大多数人工智能课程都集中在以计算机科学(CS)为中心的方法上,缺乏从哲学、神经科学、心理学、认知科学、语言学、经济学、社会科学等根源上的核心解释。在本文中,我们建议采用跨学科方法以及以cs为中心的方法来教授人工智能,其中包括为解决理解思维科学这一古老问题而建立的学科。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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