认知计算-helianghua1教学提纲.ppt

单击此处编辑母版标题样式,单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,*,*,本节标题,知识点,小点,具体内容,注释,更细详解,单击此处编辑母版标题样式,单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,*,单击此处编辑母版标题样式,单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,*,认知计算概述,何 良 华,helianghua,学习目标,认知概述,认知计算概述,认知计算经典算法,学习目标,认知概述,认知计算概述,认知计算经典算法,一、认知的定义,认知（,cognition,）是人们推测和判断客观事物的,心理过程,，是在过去的,经验,及对有关线索进行,分析,的基础上形成的,对信息的理解,、,分类,、,归纳,、,演绎和计算,认知活动包括,思维、语言、定向,和,意识,4,部分,认知反映个体的思维能力，是制定和执行护理计划的依据,1,思维,人脑对客观现实间接的、概括的反应，是认识事物本质特征及内部规律的理性认知过程。,思维活动是人类认识活动的最高形式，常通过语言文字表达,思维具有连续性，否则为思维障碍。,抽象思维、洞察力和判断力,是反映思维水平的主要指标。,2,语言,是人们进行思维的工具，是思维的物质外壳,学习,语言的技巧与环境有关,分接受性语言和表达性语言,3,定向,人们对现实的感觉，对过去、现在、将来的察觉以及对自我存在的意识。,包括时间定向、地点定向、空间定向和人物定向,是大脑功能活动的综合表现。即对环境的,知觉状态,。,4,意识,二、认知水平的评估,思维能力的评估,-,抽象思维功能,-,洞察力,-,判断力,语言能力的评估,定向力的评估,意识的评估,记忆,-,个人所经历过的事物在人脑中的反映，是人脑积累经验的功能表现。,评估方法,-,短时记忆,-,长时记忆,（一）思维能力的评估抽象思维,注意力,心理活动对一定对象的指向和集中,评估方法,-,无意注意：观察被评估者对周围环境变化的注意,-,有意注意（人类特有）：指派一些任务让被评估者完成,（一）思维能力的评估抽象思维,概念力,人脑反映客观事物本质特性的思维形式。,通过抽象概括，把握事物的本质特性而形成。,评估方法,通过数次健康教育后，请被评估者概括相关内容,（一）思维能力的评估抽象思维,理解力,对事物的理解能力。,评估方法,请被评估者按指示完成一些动作,（一）思维能力的评估抽象思维,推理力,有已知判断推出新判断的思维过程,归纳（从特殊到一般）,演绎（从一般到特殊）,评估方法,根据被评估者的年龄特征提出一定的问题,（一）思维能力的评估抽象思维,识别与理解客观事物真实性的能力,评估方法,让被评估者描述所处情形，再与实际情形作比,较看有无差异,你认为导致你来就诊的主要问题是什么？,你如何判断你目前的这种情况？,（一）思维能力的评估洞察力,肯定或否定某事物具有某种属性或某行动方案可行性的思维方式,受个体的年龄、情绪、智力、受教育水平、社会经济状况、文化背景等的影响,评估方法,展示实物让被评估者说出其属性,评价被评估者对将来打算的现实性与可行性进行评估,（一）思维能力的评估判断力,（二）语言能力的评估,语言能力是人们认知水平的重要标志，对判断个体认知水平很有价值。,（二）语言能力的评估,评估方法,-,提问,-,复述,-,自发性语言,-,命名,-,阅读,-,书写,（三）定向力的评估,时间定向力,地点定向力,空间定向力,人物定向力,定向力障碍的先后顺序依次是时间、地点、空间和人物。,意识的临床表现,（四）意识的评估,影响认知的因素,年龄,受教育水平,生活经历,文化背景,疾病,药物作用,酗酒,吸毒,认识论,比较,认知科学,认识论,比,较,认知科学,思辨,方法,实验,逻辑,工具,具体实证,单一,学科,综合,厘清思路,目标,具体验证,理论,成果,实效,七个问题,1.,认识的本质,两条认识路线的对立,2.,认识的能力,3.,认识的来源,4.,认识的过程,5.,认识的途径,6.,认识的结果及其检验,7.,认识的目的,认识论,Epistemology The Theory of Knowledge,哲学认识论,认知科学研究方向,认知科学,无所不能,学科,认知科学,最,colorful,的学科,头脑风暴,最大科学发现,认知科学,最难学科,难在何处,最大黑箱,黑箱方法,黑箱示意图,输入,输出,内部机制,已知,已知,未知,人脑,黑箱,变化,已知,对 比,推 测,伽德纳六边形,学科六边形,artificial intelligence n.,人工智能,Anthropology n.,人类学,Linguistics n.,语言学,Psychology n.,心理学,Philosophy n.,哲学,Neuroscience n.,神经系统科学,(,指神经病学、神经化学等,),学习目标,认知概述,认知计算概述,认知计算经典算法,Comparison of Silicon Computers and Carbon Computers,Digital computers are,Made from,silicon,Accurate,(essentially no errors),Fast,(nanoseconds),Execute long chains of,serial logical,operations,(billions),Irritating to humans,Comparison of Silicon Computers and Carbon Computers,Brains are,Made from,carbon compounds,Inaccurate,(low precision,noisy),Slow,(milliseconds,10,6,times slower),Execute,short,chains of,parallel alogical,associative operations,(perhaps 10 operations),Understandable to humans,Performance of Silicon Computers and Carbon Computer,Huge disadvantage,for carbon:more than,10,12,in the product of speed and power.,But we do,better and faster,than them in many tasks:,speech recognition,object recognition,face recognition,motor control,most complex memory functions,information integration,.,Implication:Cognitive“software”uses,only a few but very powerful,elementary operations.,Why Build a Brain-Like Computer?,1.Engineering,.,Computers are all special purpose devices.,Many of the important practical computer applications of the next few decades will be,cognitive:,Language understanding.,Internet search.,Cognitive data mining.,Decent human-computer interfaces.,We feel it will be necessary to have a,brain-like architecture,to run these applications,efficiently,.,2.Kinship Recognition,Human Factors,:,To be,recognized,as intelligent by humans,a machine has to have a somewhat human-like intelligence.,There may be many kinds of intelligence,but we can only understand and communicate with one of them!,Successful,human-computer interactions,will require a brain-like computer doing cognitive computation.,“,If oxen and horses had hands and could create works of art,horses would draw pictures of gods like horses and oxen,gods like oxen”,Xenophanes(C.530 B.C.E.),3.Personal,:,It would be the ultimate cool gadget.,A technological vision:,In 2050 the personal computer you buy in Wal-Mart will have,two CPUs,with very different architecture:,First,a traditional,von Neumann machine,that runs spreadsheets,does word processing,keeps your calendar straight,etc.What they do now.,Second,a,brain-like chip,To handle the interface with the von Neumann machine,Give you the data that you need from the Web or your files(but didnt think to ask for).,Be your silicon friend,guide,and confidant,.,History:Technical Issues,Many have proposed the construction of brain-like computers for cognitive computation.,These attempts usually start with,massively parallel arrays of neural computing elements,elements based to some degree on biological neurons,the layered 2-D anatomy of mammalian cerebral cortex.,Such attempts have failed commercially.,The early,connection machines,from,Thinking Machines,Inc.,(W.D.Hillis,The Connection Machine,1987)was the most nearly successful commercially.,Consider the extremes of computational brain models:,First Extreme:Biological Realism,The human brain is composed of on the order of,10,10,neurons,connected together with at least,10,14,neural connections.(Probably underestimates.),Biological neurons and their connections are,extremely complex electrochemical structures,.The,more realistic,the neuron approximation,the smaller,the network that can be modeled.,There is very good evidence that for cerebral cortex,a bigger brain is a better brain.,Projects that model neurons are of scientific interest.,They are not large enough to model or simulate interesting cognition.,Neural Networks.,The most successful brain inspired models are,neural networks,.,They are built from simple approximations of biological neurons:nonlinear integration of many weighted inputs.,Throw out all the other biological detail.,Cognitive computation is based on useful approximations.,Second Extreme:Associatively Linked Networks,.,The second class of brain-like computing approximations is a basic part of computer science:,Associatively linked structures,.,One example of such a structure is a semantic network.,Such structures underlie most of the practically successful applications of artificial intelligence.,Associatively Linked Networks,(2),The connection between the biological nervous system and such a structure is unclear.,Few believe that,nodes,in a semantic network correspond to single neurons or groups of neurons.,Nodes are composed of many parts and contain,significant internal structure,.,Physiology(fMRI)shows that a complex cognitive structure a word,for instance gives rise to,widely distributed cortical activation,.,Virtue of Linked Networks:,They have sparsely connected nodes.,In practical systems,the,number of links converging on a node,range from one or two up to a dozen or so.,Look at Some Examples,The brain(and cognitive computation)do things differently:,If you build a brain expect to get,weaknesses,as well as,strengths,.,Both strengths and weaknesses are,intrinsic to the hardware itself.,Give a few examples.,Cognitive Strengths,Strengths:,Ability to,approximate,complex events in useful ways(using words,concepts).,Ability to,integrate,information from many sources.,Effective,search,of a large memory,that is,integration of past experience with the present situation,.,Tight,coupling,of higher-level cognition with perception,Non-logical processes such as“,intuition,”for prediction and understanding.,Cognitive Weaknesses,Weaknesses:,High error rate,.,Slow,responses compared to silicon time scales.,Alogical,information processing,for example,association,.,One result:,Great difficulty with logic and formal reasoning.,Loss of detail,in memory storage.,Interference,from other memories.,Prejudice(jumping to conclusions),.,Lack of,explanation,for actions.,Conclusions,Brains are very different in their basic,style,of computation than computers.,They work largely with,memory,sensory,and perceptually based,information.,They are,not logical,.,They,integrate information,from many sources.,They,approximate,a complex world using entities like,words and concepts,.,They work effectively with,relationships,.,They use,context,effectively.,They can work quickly and effectively with,very large memories,.,Conclusions,Many of the these,style,differences arise from the necessities arising from,grossly different hardware,.,They compute the different ways they do because,they have to,!,Brains and computers are,complementary,in their strengths and weaknesses.,But:we already have,computer-like,computers.,If we want to do real,cognitive computation,we need to build,brain-like,computers!,学习目标,认知概述,认知计算概述,认知计算经典算法,