斯坦福大學公開課 機器學習 講師介紹

瀏覽：52 | 發布于：2010.12.16 | 分類：默認分類

講師介紹：

Andrew的研究領域是機器學習和人工智能。他是STAIR（斯坦福人工智能機器人）項目的負責人，該項目以研發可整理房間、操作洗完機、取放物品和做飯的輔助家務機器人為目標。從1956年起的AI夢已經慢慢成形，表現出“廣譜”的智力。現在，人工智能已經進入了許多分支學科，諸如機器學習，視覺、導航、推理、計劃和自然語言處理等。為了實現輔助家務機器人的目標，STAIR將這些所有學科的應用集合為一個單獨的平臺工具。這與之前在各個字學科內的單獨研究截然不同，STAIR把AI研究推向真正綜合的人工智能。

Andrew的另一個研究點是機器人控制的機器學習算法，依靠human hand-engineering建立控制器，從而實現機器人的自我學習與自我控制。運用這種方法，Ng的團隊已經研發出最先進的自動直升飛機控制器，能夠實現許多人類飛行員都感覺非常困難的特技飛行。作為這項工作的一部分，他的團隊還研發出了能夠將單幅圖像轉換為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.