斯坦福大学公开课 机器学习 讲师介绍
浏览：52 | 发布于：2010.12.16 | 分类：默认分类
讲师介绍：
Andrew的研究领域是机器学习和人工智能。他是STAIR（斯坦福人工智能机器人）项目的负责人，该项目以研发可整理房间、操作洗完机、取放物品和做饭的辅助家务机器人为目标。从1956年起的AI梦已经慢慢成形，表现出“广谱”的智力。现在，人工智能已经进入了许多分支学科，诸如机器学习，视觉、导航、推理、计划和自然语言处理等。为了实现辅助家务机器人的目标，STAIR将这些所有学科的应用集合为一个单独的平台工具。这与之前在各个字学科内的单独研究截然不同，STAIR把AI研究推向真正综合的人工智能。
Andrew的另一个研究点是机器人控制的机器学习算法，依靠human hand-engineering建立控制器，从而实现机器人的自我学习与自我控制。运用这种方法，Ng的团队已经研发出最先进的自动直升飞机控制器，能够实现许多人类飞行员都感觉非常困难的特技飞行。作为这项工作的一部分，他的团队还研发出了能够将单幅图像转换为3D模型的算法。
Ng’s research is in the areas of machine learning and artificial intelligence. He leads the STAIR (STanford Artificial Intelligence Robot) project, whose goal is to develop a home assistant robot that can perform tasks such as tidy up a room, load/unload a dishwasher, fetch and deliver items, and prepare meals using a kitchen. Since its birth in 1956, the AI dream has been to build systems that exhibit "broad spectrum" intelligence. However, AI has since splintered into many different subfields, such as machine learning, vision, navigation, reasoning, planning, and natural language processing. To realize its vision of a home assistant robot, STAIR will unify into a single platform tools drawn from all of these AI subfields. This is in distinct contrast to the 30-year-old trend of working on fragmented AI sub-fields, so that STAIR is also a unique vehicle for driving forward research towards true, integrated AI.
Ng also works on machine learning algorithms for robotic control, in which rather than relying on months of human hand-engineering to design a controller, a robot instead learns automatically how best to control itself. Using this approach, Ng’s group has developed by far the most advanced autonomous helicopter controller, that is capable of flying spectacular aerobatic maneuvers that even experienced human pilots often find extremely difficult to execute. As part of this work, Ng’s group also developed algorithms that can take a single image,and turn the picture into a 3-D model that one can fly-through and see from different angles.
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