簡(jiǎn)介：20202020國(guó)考申論范文學(xué)好“磨”字訣書寫精彩人生國(guó)考申論范文學(xué)好“磨”字訣書寫精彩人生善用人工智能善用人工智能創(chuàng)造美好生活（兩篇）創(chuàng)造美好生活（兩篇）學(xué)好“磨”字訣書寫精彩人生學(xué)好“磨”字訣書寫精彩人生磨，是好事多磨的樂觀磨，是切磋琢磨的專研磨，是鐵杵磨針的堅(jiān)持。隨著時(shí)代不斷進(jìn)步，給年輕人帶來機(jī)遇的同時(shí)更多帶來的是挑戰(zhàn)，如今，競(jìng)爭(zhēng)日趨激烈，生存壓力不斷加大，對(duì)年輕人要求能力更高。只有學(xué)會(huì)打磨自己，不斷提升自己，在當(dāng)今社會(huì)找到自己的精神坐標(biāo)。所以，掌握好好“磨”字訣，書寫精彩人生。打磨自身學(xué)會(huì)理性，書寫精彩人生。打磨自己是一種務(wù)實(shí)的精神，是一種理性的選擇。如今成功學(xué)倍受追捧，一朝成名、一夜暴富成為每一個(gè)青年的理想追求，社會(huì)風(fēng)氣日漸浮躁。但是有一個(gè)人卻能守住內(nèi)心，以理性思考人生，以提升自我彰顯風(fēng)采，那就是屠呦呦。在學(xué)術(shù)界熱衷于發(fā)表論文、申請(qǐng)項(xiàng)目、相互比較出版書籍的浮躁風(fēng)氣下，屠呦呦沉下心來理性認(rèn)識(shí)自己發(fā)展的道路，全身心投入青蒿素的研制中，十年磨一劍，查閱無數(shù)資料，經(jīng)歷無數(shù)試驗(yàn)，終于為人類健康帶來新的希望。成功看似簡(jiǎn)單，其實(shí)需要每個(gè)人的不斷付出。社會(huì)多姿多彩，充滿誘惑，容易迷茫。人的精力有限的，只能通過專研深入一行，找準(zhǔn)自己的方向，矢志不渝為奮斗，從智能導(dǎo)診機(jī)器人到人臉識(shí)別技術(shù)，從智能語音技術(shù)到智能醫(yī)療診斷人工智能這場(chǎng)巨大的科學(xué)革命，深刻地改變著人類的生產(chǎn)生活方式，推動(dòng)著經(jīng)濟(jì)社會(huì)的發(fā)展。然而，在人工智能快速發(fā)展的同時(shí)，也帶來機(jī)器殺人等發(fā)展倫理問題，正如很多人擔(dān)憂的那樣，人類會(huì)不會(huì)被人工智能所控制。因此，只有處理好人類與技術(shù)的關(guān)系，善用人工智能，才能真正發(fā)揮人工智能的科學(xué)魅力。善用人工智能，讓人工智能引領(lǐng)新生活革命。善用人工智能，讓人工智能引領(lǐng)新生活革命。一部人類的發(fā)展史就是一部科技進(jìn)步的歷史，科技改變著人們的生活方式，沒有科技，就沒有今天的幸福生活。智能導(dǎo)診機(jī)器人讓病人就醫(yī)咨詢更為便利智能腕表的“圍欄服務(wù)”讓子女對(duì)老人安全更加放心智能掃地機(jī)器人讓家庭主婦省心省力人工智能已悄然融入到日常生活的方方面面，并極大地節(jié)省了人力成本，提高工作效率，豐富著人們的物質(zhì)與精神生活。因此，我們堅(jiān)持“技術(shù)應(yīng)服務(wù)于人類”的理念，加快人工智能在生活領(lǐng)域的布局，讓人工智能引領(lǐng)新的生活革命。善用人工智能，讓人工智能引領(lǐng)新行業(yè)革命。善用人工智能，讓人工智能引領(lǐng)新行業(yè)革命。新一代人工智能技術(shù)，對(duì)傳統(tǒng)產(chǎn)業(yè)的滲透廣度、深度是前所未有的。以騰訊、百度等為代表互聯(lián)網(wǎng)巨頭，爭(zhēng)相布局人工智能，推動(dòng)智能家居、智能安防等行業(yè)的加速發(fā)展。但與此同時(shí)，當(dāng)前產(chǎn)業(yè)界和資本界浮躁風(fēng)氣盛行，很多人利用人工智能的概念去炒作、去申請(qǐng)補(bǔ)貼等等，這勢(shì)必不利于人工智能本身的發(fā)展。因此，作為企業(yè)必須樹立正確的發(fā)展觀念，不斷加快技術(shù)創(chuàng)新，積極主動(dòng)地尋找人工智能技術(shù)的應(yīng)用場(chǎng)

簡(jiǎn)介：內(nèi)容提要人工智能與司法的深度融合，既體現(xiàn)在案件的法律適用環(huán)節(jié)也體現(xiàn)在事實(shí)認(rèn)定環(huán)節(jié)，而事實(shí)認(rèn)定是法律適用的前提。人工智能對(duì)案件事實(shí)認(rèn)定的介入，需要將證據(jù)數(shù)據(jù)化、對(duì)數(shù)據(jù)進(jìn)行運(yùn)算整合、輸出人可以理解的結(jié)論。在證據(jù)數(shù)據(jù)化環(huán)節(jié)，需要對(duì)證據(jù)進(jìn)行結(jié)構(gòu)化的數(shù)據(jù)改造，并克服語言障礙。在數(shù)據(jù)整合環(huán)節(jié)，人工智能主要以概率推理而不是因果推理作為邏輯推理方式，其算法也需要面對(duì)可計(jì)算性與復(fù)雜性兩大難題。在結(jié)論輸出環(huán)節(jié)，需要解決機(jī)器學(xué)習(xí)如何深化、信念如何建立與機(jī)器如何表達(dá)等難題。人工智能融入案件事實(shí)認(rèn)定所面臨的這些主要難題，可以嘗試通過“小數(shù)據(jù)”訓(xùn)練，逐步構(gòu)建人工智能“心智微結(jié)構(gòu)”去慢慢攻克。關(guān)鍵詞關(guān)鍵詞人工智能；事實(shí)認(rèn)定；心智微結(jié)構(gòu)；小數(shù)據(jù)目錄目錄引言一、證據(jù)數(shù)據(jù)化結(jié)構(gòu)化改造與語言難題二、數(shù)據(jù)整合推理與算法三、智能的深化與輸出學(xué)習(xí)、信念與表達(dá)結(jié)語引言引言從世界范圍看，人工智能正從四個(gè)層面由淺入深地介入司法。一是逐步代替人力從事法條查詢、案例檢索、案件分類、庭審錄入等相對(duì)簡(jiǎn)單機(jī)械、重復(fù)性高的工作。二是作為助理，完成司法咨詢、合同審核、證據(jù)獲取、裁判文書輔助生成等輔助性任務(wù)。三是對(duì)海量裁判文書進(jìn)行統(tǒng)計(jì)分析并作出預(yù)測(cè)，為法官裁判提供參考信息。四是直接參與決策或進(jìn)行局部裁判，比如進(jìn)行再犯風(fēng)險(xiǎn)評(píng)估、嫌疑人逃脫可能性判斷、合理量刑測(cè)算等。2016年，美國(guó)法院通過對(duì)“威斯康星州訴盧米斯”（WISCONSINVLOOMIS）案的判決，正式承認(rèn)了人工智能參與量刑裁判的合理性與正當(dāng)性。由于量刑本身就是裁判的一部分，這意味著目前的人工智能已經(jīng)不僅僅充當(dāng)一種輔助性工具，它對(duì)司法的影響正逐漸進(jìn)入實(shí)質(zhì)層面，試圖介入司法的核心裁判。律人工智能在現(xiàn)階段及未來的努力方向。一、證據(jù)數(shù)據(jù)化結(jié)構(gòu)化改造與語言難題人工智能介入事實(shí)認(rèn)定的第一步，是供給人工智能可分析的數(shù)字化信息，即將全案信息轉(zhuǎn)化為數(shù)據(jù)。然而，案件事實(shí)基礎(chǔ)是證據(jù)，證據(jù)是實(shí)體而非數(shù)據(jù)。證據(jù)數(shù)據(jù)化是人工智能介入事實(shí)認(rèn)定的先決條件。（一）證據(jù)如何變數(shù)據(jù)就人類認(rèn)知而言，我們可以直接感知并理解實(shí)體證據(jù)，無論它以怎樣的形態(tài)呈現(xiàn)。人類的感官系統(tǒng)、思維系統(tǒng)、表意系統(tǒng)等為接受各類證據(jù)提供了工具，使我們抓取證明信息不受證據(jù)樣態(tài)的限制。但對(duì)人工智能而言，證據(jù)形態(tài)將成為信息輸入的第一障礙。計(jì)算機(jī)如何理解一張照片的含義或一段視頻的內(nèi)容“一把帶血的刀子”如何進(jìn)入電腦，使電腦意識(shí)到這把刀子的證明信息及價(jià)值解決這一問題須深入證據(jù)結(jié)構(gòu)之中?，F(xiàn)實(shí)世界里的證據(jù)都是“塊結(jié)構(gòu)”的，即不可拆分的完整一塊。一個(gè)證據(jù)就是“一個(gè)整塊”。比如，“一把帶血的刀子”作為一個(gè)獨(dú)立的證據(jù)，不能拆分成“血液”“刀子”。當(dāng)然，該證據(jù)包含豐富的證明信息，如被害人的血液、加害人的指紋、加害人用刀殺害被害人的因果關(guān)聯(lián)等；該證據(jù)與其他證據(jù)關(guān)聯(lián)還會(huì)產(chǎn)生新的信息，如被害人傷口與刀刃的吻合情況。一個(gè)證據(jù)究竟包含多少證明信息、哪些對(duì)裁判有效、哪些無效或應(yīng)予排除，依賴裁判者的自我感知與主觀判斷，不同的人會(huì)作出不同的考量和取舍。由于內(nèi)含信息的不確定與變動(dòng)性，該證據(jù)從證明內(nèi)容上并不能被隨意拆分，出于任何理由的拆分都只是基于個(gè)體化的認(rèn)知，不具有普適性。最好的方法是將這一整塊證據(jù)展示到裁判者面前，由其自由心證。由于裁判者無需解釋是否采信、采信多少，只要該證據(jù)曾呈現(xiàn)于裁判者面前，就視為裁判者已經(jīng)窮盡了對(duì)該證據(jù)的全面思考，充分吸收了它的證明價(jià)值于裁判之中。可見，證據(jù)的“塊結(jié)構(gòu)”既符合物理形態(tài)上的視覺空間要求，又滿足內(nèi)在證明信息上的完整性標(biāo)準(zhǔn)，更有利于遮蔽司法裁判上的種種被動(dòng)與不確定。但是，這把刀子擺在計(jì)算機(jī)面前并不會(huì)產(chǎn)生上述效果。現(xiàn)階段，計(jì)算機(jī)尚無法直接理解“塊結(jié)構(gòu)”的證據(jù)，只能運(yùn)用計(jì)算機(jī)可理解的語言將“塊結(jié)構(gòu)”擊破打散，形成數(shù)字化、可識(shí)別的結(jié)構(gòu)性數(shù)據(jù)，以獲得其中的有效信息。計(jì)算機(jī)可理解的語言一般有三層以0和1為基礎(chǔ)的二進(jìn)制機(jī)器語言，可識(shí)別并

簡(jiǎn)介：2021年公需科目公需科目人工智能與健康考試題人工智能與健康考試題庫(kù)試題及答案庫(kù)試題及答案一一、單項(xiàng)選擇題1、的文化是長(zhǎng)治久安的治國(guó)方略，是實(shí)施理想抱負(fù)的平臺(tái)。A、修之于身B、修之于家C、修之于鄉(xiāng)D、修之于天下請(qǐng)選擇本題答案ABCD正確答案C2、一般數(shù)據(jù)保護(hù)法案中對(duì)個(gè)人數(shù)據(jù)泄露的規(guī)定是數(shù)據(jù)控制者應(yīng)在小時(shí)之內(nèi)向監(jiān)管機(jī)構(gòu)報(bào)告?zhèn)€人數(shù)據(jù)的泄露情況。A、24B、48C、72D、96請(qǐng)選擇本題答案第1頁共15頁ABCD正確答案C3、本課程使用小孩早飯吃不好的案例，來解釋了。A、因果圖B、排列圖C、流程圖D、控制圖請(qǐng)選擇本題答案ABCD正確答案A4、根據(jù)本講，是社會(huì)的基本細(xì)胞。A、家庭B、學(xué)校C、基層D、國(guó)家請(qǐng)選擇本題答案ABCD正確答案A5、根據(jù)本講，是在網(wǎng)絡(luò)搜索、網(wǎng)絡(luò)識(shí)別、網(wǎng)址識(shí)別當(dāng)中用到的一種特殊的標(biāo)志和符號(hào)。A、網(wǎng)站實(shí)名B、域名C、元標(biāo)識(shí)D、網(wǎng)頁標(biāo)識(shí)請(qǐng)選擇本題答案第2頁共15頁ABCD正確答案C6、根據(jù)本講，對(duì)于國(guó)來說，鄉(xiāng)是。A、社會(huì)化環(huán)境B、最基層的政府C、生活成長(zhǎng)的故鄉(xiāng)D、為民服務(wù)的天地請(qǐng)選擇本題答案ABCD正確答案B個(gè)重要方向。A、智慧醫(yī)療B、科技醫(yī)療C、居家醫(yī)療D、以上都對(duì)請(qǐng)選擇本題答案ABCD正確答案A13、本講強(qiáng)調(diào)人工智能技術(shù)通過影像識(shí)別分類、分析診斷，結(jié)合電子病歷及臨床診斷數(shù)據(jù)，幫助醫(yī)生做出診斷決策，降低了主觀誤診率，提高了。A、經(jīng)濟(jì)效益B、治療效果C、經(jīng)濟(jì)效益和治療效果D、以上都不對(duì)請(qǐng)選擇本題答案ABCD正確答案C14、本課程指出，互聯(lián)網(wǎng)最大的優(yōu)勢(shì)是能夠。A、精準(zhǔn)匹配第5頁共15頁B、精準(zhǔn)分診C、精確診療D、以上都對(duì)請(qǐng)選擇本題答案ABCD正確答案D15、根據(jù)本講，互聯(lián)網(wǎng)醫(yī)院是我們國(guó)家的。A、發(fā)展戰(zhàn)略B、發(fā)展方向C、發(fā)展基礎(chǔ)D、以上都不對(duì)請(qǐng)選擇本題答案ABCD正確答案A16、本講從兩方面分析企業(yè)質(zhì)量成本戰(zhàn)略可以推動(dòng)企業(yè)產(chǎn)品質(zhì)量的提高。A、質(zhì)量B、成本C、質(zhì)量、成本D、以上都不對(duì)請(qǐng)選擇本題答案ABCD正確答案C17、根據(jù)本講，只有在外部損失統(tǒng)計(jì)之后再加入以后，我們才可以去分析所占的比例。第6頁共15頁A、預(yù)防成本B、鑒定成本C、預(yù)防成本和鑒定成本D、以上都不對(duì)請(qǐng)選擇本題答案ABCD正確答案C18、根據(jù)本講，我國(guó)成人高血壓患病在20XX年達(dá)到。A、2480B、2580C、2680D、2780請(qǐng)選擇

簡(jiǎn)介：共需科目共需科目2020共需科目人工智能與健康考共需科目人工智能與健康考試及答案（及答案（95分）分）單選單選11956年之前，人工智能的發(fā)展處于（）。（20分）A萌芽期B第一次繁榮期C第一次低谷期D復(fù)蘇期我的答案A√答對(duì)2環(huán)境與健康息息相關(guān)，保護(hù)環(huán)境（）健康。（20分）A發(fā)展B重塑C促進(jìn)D催生我的答案C√答對(duì)319世紀(jì)20年代，英國(guó)科學(xué)家（）設(shè)計(jì)了第一架“計(jì)算機(jī)器”，它被認(rèn)為是計(jì)算機(jī)硬件，也是人工智能硬件的前身。（20分）A笛卡爾B奧古斯塔斯德摩根B戰(zhàn)場(chǎng)機(jī)器人C智能地雷D智能魚雷我的答案B√答對(duì)7當(dāng)我們需要尋求健康咨詢服務(wù)時(shí)，應(yīng)該撥打的熱線電話是（）。（20分）A12315B12301C12345D12320我的答案D√答對(duì)8中國(guó)公民健康素養(yǎng)66條提倡，孩子出生后應(yīng)當(dāng)盡早開始母乳喂養(yǎng)，滿（）個(gè)月時(shí)合理添加輔食。（20分）A5B6C7D8我的答案B√答對(duì)9（）機(jī)器人無需人的干預(yù)，能夠在各種環(huán)境下自動(dòng)完成各項(xiàng)擬人任務(wù)。（20分）A傳感型B交互型

簡(jiǎn)介：ICS31200L56YD/TYD/T中華人民共和國(guó)通信行業(yè)標(biāo)準(zhǔn)釣魚網(wǎng)站監(jiān)測(cè)與處置系統(tǒng)企業(yè)側(cè)系統(tǒng)能力要求人工智能芯片基準(zhǔn)測(cè)試評(píng)估方法EVALUATIONMETHODFORARTIFICIALINTELLIGENCECHIPBENCHMARK（報(bào)批稿）發(fā)布實(shí)施中華人民共和國(guó)工業(yè)和信息化部發(fā)布YD/TXXXXXXXX前言本文件按照GB/T112020給出的規(guī)則起草。本標(biāo)準(zhǔn)由中國(guó)通信標(biāo)準(zhǔn)化協(xié)會(huì)提出并歸口。請(qǐng)注意本標(biāo)準(zhǔn)的某些內(nèi)容可能涉及專利。本標(biāo)準(zhǔn)的發(fā)布機(jī)構(gòu)不承擔(dān)識(shí)別這些專利的責(zé)任。本標(biāo)準(zhǔn)起草單位中國(guó)信息通信研究院、南京新一代人工智能研究院、西安交通大學(xué)人工智能與機(jī)器人研究所、華為技術(shù)有限公司、深圳市騰訊計(jì)算機(jī)系統(tǒng)有限公司、阿里云計(jì)算有限公司、深圳鯤云信息科技有限公司、清華大學(xué)、安謀科技中國(guó)有限公司、中科寒武紀(jì)科技股份有限公司、賽靈思電子科技（北京）有限公司、英特爾（中國(guó)）有限公司、穎脈信息技術(shù)（上海）有限公司、上海海思技術(shù)有限公司、北京百度網(wǎng)訊科技有限公司、上海燧原科技有限公司、北京地平線機(jī)器人技術(shù)研發(fā)有限公司本標(biāo)準(zhǔn)主要起草人張蔚敏、劉碩、張哲煜、孫明俊、任鵬舉、關(guān)賀、于瀟宇、張龍、游亮、潘逢治、劉建航、杜子?xùn)|、汪玉、葛廣君、葉挺群、沈林杰、牛昕宇、鄭魁、張亞軍、高劍林、章恒、方紹峽、王凱、李億、徐劍威、石恒、羅航、曾洪博、程智鋒。

簡(jiǎn)介：字?jǐn)?shù)英文字?jǐn)?shù)英文28872887單詞，單詞，1640016400字符；中文字符；中文54305430漢字漢字出處出處STUARTSTUARTRUSSELL,DANIELRUSSELL,DANIELDEWEY,MAXDEWEY,MAXTEGMARKRESEARCHTEGMARKRESEARCHPRIORITIESPRIORITIESFORFORROBUSTROBUSTANDANDBENEFICIALBENEFICIALARTIFICIALARTIFICIALINTELLIGENCEJASSOCIATIONINTELLIGENCEJASSOCIATIONFORFORTHETHEADVANCEMENTADVANCEMENTOFOFARTIFICIALARTIFICIALINTELLIGENCE2015,364105114INTELLIGENCE2015,364105114外文文獻(xiàn)外文文獻(xiàn)RESEARCHPRIORITIESFORROBUSTANDBENEFICIALARTIFICIALINTELLIGENCEABSTRACTSUCCESSINTHEQUESTFORARTIFICIALINTELLIGENCEHASTHEPOTENTIALTOBRINGUNPRECEDENTEDBENEFITSTOHUMANITY,ANDITISTHEREFOREWORTHWHILETOINVESTIGATEHOWTOMAXIMIZETHESEBENEFITSWHILEAVOIDINGPOTENTIALPITFALLSTHISARTICLEGIVESNUMEROUSEXAMPLESWHICHSHOULDBYNOMEANSBECONSTRUEDASANEXHAUSTIVELISTOFSUCHWORTHWHILERESEARCHAIMEDATENSURINGTHATAIREMAINSROBUSTANDBENEFICIALKEYWORDSARTIFICIALINTELLIGENCE,SUPERINTELLIGENCE,ROBUST,BENEFICIAL,SAFETY,SOCIETYARTIFICIALINTELLIGENCEAIRESEARCHHASEXPLOREDAVARIETYOFPROBLEMSANDAPPROACHESSINCEITSINCEPTION,BUTFORTHELAST20YEARSORSOHASBEENFOCUSEDONTHEPROBLEMSSURROUNDINGTHECONSTRUCTIONOFINTELLIGENTAGENTS–SYSTEMSTHATPERCEIVEANDACTINSOMEENVIRONMENTINTHISCONTEXT,THECRITERIONFORINTELLIGENCEISRELATEDTOSTATISTICALANDECONOMICNOTIONSOFRATIONALITY–COLLOQUIALLY,THEABILITYTOMAKEGOODDECISIONS,PLANS,ORINFERENCESTHEADOPTIONOFPROBABILISTICREPRESENTATIONSANDSTATISTICALLEARNINGMETHODSHASLEDTOALARGEDEGREEOFINTEGRATIONANDCROSSFERTILIZATIONBETWEENAI,MACHINELEARNING,STATISTICS,CONTROLTHEORY,NEUROSCIENCE,ANDOTHERFIELDSTHEESTABLISHMENTOFSHAREDTHEORETICALFRAMEWORKS,COMBINEDWITHBYNOMEANSBEINTERPRETEDASANEXHAUSTIVELISTLABORMARKETFORECASTINGWHENANDINWHATORDERSHOULDWEEXPECTVARIOUSJOBSTOBECOMEAUTOMATEDFREYANDOSBORNE2013HOWWILLTHISAFFECTTHEWAGESOFLESSSKILLEDWORKERS,THECREATIVEPROFESSIONS,ANDDIFFERENTKINDSOFINFORMATIONWORKERSSOMEHAVEHAVEARGUEDTHATAIISLIKELYTOGREATLYINCREASETHEOVERALLWEALTHOFHUMANITYASAWHOLEBRYNJOLFSSONANDMCAFEE2014HOWEVER,INCREASEDAUTOMATIONMAYPUSHINCOMEDISTRIBUTIONFURTHERTOWARDSAPOWERLAWBRYNJOLFSSON,MCAFEE,ANDSPENCE2014,ANDTHERESULTINGDISPARITYMAYFALLDISPROPORTIONATELYALONGLINESOFRACE,CLASS,ANDGENDERRESEARCHANTICIPATINGTHEECONOMICANDSOCIETALIMPACTOFSUCHDISPARITYCOULDBEUSEFULOTHERMARKETDISRUPTIONSSIGNIFICANTPARTSOFTHEECONOMY,INCLUDINGFINANCE,INSURANCE,ACTUARIAL,ANDMANYCONSUMERMARKETS,COULDBESUSCEPTIBLETODISRUPTIONTHROUGHTHEUSEOFAITECHNIQUESTOLEARN,MODEL,ANDPREDICTHUMANANDMARKETBEHAVIORSTHESEMARKETSMIGHTBEIDENTIFIEDBYACOMBINATIONOFHIGHCOMPLEXITYANDHIGHREWARDSFORNAVIGATINGTHATCOMPLEXITYMANYIKAETAL2013POLICYFORMANAGINGADVERSEEFFECTSWHATPOLICIESCOULDHELPINCREASINGLYAUTOMATEDSOCIETIESFLOURISHFOREXAMPLE,BRYNJOLFSSONANDMCAFEEBRYNJOLFSSONANDMCAFEE2014EXPLOREVARIOUSPOLICIESFORINCENTIVIZINGDEVELOPMENTOFLABORINTENSIVESECTORSANDFORUSINGAIGENERATEDWEALTHTOSUPPORTUNDEREMPLOYEDPOPULATIONSWHATARETHEPROSANDCONSOFINTERVENTIONSSUCHASEDUCATIONALREFORM,APPRENTICESHIPPROGRAMS,LABORDEMANDINGINFRASTRUCTUREPROJECTS,ANDCHANGESTOMINIMUMWAGELAW,TAXSTRUCTURE,ANDTHESOCIALSAFETYNETGLAESER2014HISTORYPROVIDESMANYEXAMPLESOFSUBPOPULATIONSNOTNEEDINGTOWORKFORECONOMICSECURITY,RANGINGFROMARISTOCRATSINANTIQUITYTOMANYPRESENTDAYCITIZENSOFQATARWHATSOCIETALSTRUCTURESANDOTHERFACTORSDETERMINEWHETHERSUCHPOPULATIONSFLOURISHUNEMPLOYMENTISNOTTHESAMEASLEISURE,ANDTHEREAREDEEPLINKSBETWEENUNEMPLOYMENTANDUNHAPPINESS,SELFDOUBT,ANDISOLATIONHETSCHKO,KNABE,ANDSCHO¨B2014CLARKANDOSWALD1994UNDERSTANDINGWHATPOLICIESANDNORMSCAN

簡(jiǎn)介：ARTICLESWINTER2015105ARTIFICIALINTELLIGENCEAIRESEARCHHASEXPLOREDAVARIETYOFPROBLEMSANDAPPROACHESSINCEITSINCEPTION,BUTFORTHELAST20YEARSORSOHASBEENFOCUSEDONTHEPROBLEMSSURROUNDINGTHECONSTRUCTIONOFINTELLIGENTAGENTSSYSTEMSTHATPERCEIVEANDACTINSOMEENVIRONMENTINTHISCONTEXT,THECRITERIONFORINTELLIGENCEISRELATEDTOSTATISTICALANDECONOMICNOTIONSOFRATIONALITYCOLLOQUIALLY,THEABILITYTOMAKEGOODDECISIONS,PLANS,ORINFERENCESTHEADOPTIONOFPROBABILISTICREPRESENTATIONSANDSTATISTICALLEARNINGMETHODSHASLEDTOALARGEDEGREEOFINTEGRATIONANDCROSSFERTILIZATIONBETWEENAI,MACHINELEARNING,STATISTICS,CONTROLTHEORY,NEUROSCIENCE,ANDOTHERFIELDSTHEESTABLISHMENTOFSHAREDTHEORETICALFRAMEWORKS,COMBINEDWITHTHEAVAILABILITYOFDATAANDPROCESSINGPOWER,HASYIELDEDREMARKABLESUCCESSESINVARIOUSCOMPONENTTASKSSUCHASSPEECHRECOGNITION,IMAGECLASSIFICATION,AUTONOMOUSVEHICLES,MACHINETRANSLATION,LEGGEDLOCOMOTION,ANDQUESTIONANSWERINGSYSTEMSCOPYRIGHT?2015,ASSOCIATIONFORTHEADVANCEMENTOFARTIFICIALINTELLIGENCEALLRIGHTSRESERVEDISSN07384602RESEARCHPRIORITIESFORROBUSTANDBENEFICIALARTIFICIALINTELLIGENCESTUARTRUSSELL,DANIELDEWEY,MAXTEGMARKNSUCCESSINTHEQUESTFORARTIFICIALINTELLIGENCEHASTHEPOTENTIALTOBRINGUNPRECEDENTEDBENEFITSTOHUMANITY,ANDITISTHEREFOREWORTHWHILETOINVESTIGATEHOWTOMAXIMIZETHESEBENEFITSWHILEAVOIDINGPOTENTIALPITFALLSTHISARTICLEGIVESNUMEROUSEXAMPLESWHICHSHOULDBYNOMEANSBECONSTRUEDASANEXHAUSTIVELISTOFSUCHWORTHWHILERESEARCHAIMEDATENSURINGTHATAIREMAINSROBUSTANDBENEFICIALARTICLESWINTER2015107ECONOMICMEASURESITISPOSSIBLETHATECONOMICMEASURESSUCHASREALGDPPERCAPITADONOTACCURATELYCAPTURETHEBENEFITSANDDETRIMENTSOFHEAVILYAIANDAUTOMATIONBASEDECONOMIES,MAKINGTHESEMETRICSUNSUITABLEFORPOLICYPURPOSESMOKYR2014RESEARCHONIMPROVEDMETRICSCOULDBEUSEFULFORDECISIONMAKINGLAWANDETHICSRESEARCHTHEDEVELOPMENTOFSYSTEMSTHATEMBODYSIGNIFICANTAMOUNTSOFINTELLIGENCEANDAUTONOMYLEADSTOIMPORTANTLEGALANDETHICALQUESTIONSWHOSEANSWERSAFFECTBOTHPRODUCERSANDCONSUMERSOFAITECHNOLOGYTHESEQUESTIONSSPANLAW,PUBLICPOLICY,PROFESSIONALETHICS,ANDPHILOSOPHICALETHICS,ANDWILLREQUIREEXPERTISEFROMCOMPUTERSCIENTISTS,LEGALEXPERTS,POLITICALSCIENTISTS,ANDETHICISTSFOREXAMPLELIABILITYANDLAWFORAUTONOMOUSVEHICLESIFSELFDRIVINGCARSCUTTHEROUGHLY40,000ANNUALUSTRAFFICFATALITIESINHALF,THECARMAKERSMIGHTGETNOT20,000THANKYOUNOTES,BUT20,000LAWSUITSINWHATLEGALFRAMEWORKCANTHESAFETYBENEFITSOFAUTONOMOUSVEHICLESSUCHASDRONEAIRCRAFTANDSELFDRIVINGCARSBESTBEREALIZEDVLADECK2014SHOULDLEGALQUESTIONSABOUTAIBEHANDLEDBYEXISTINGSOFTWAREANDINTERNETFOCUSEDCYBERLAW,ORSHOULDTHEYBETREATEDSEPARATELYCALO2014BINBOTHMILITARYANDCOMMERCIALAPPLICATIONS,GOVERNMENTSWILLNEEDTODECIDEHOWBESTTOBRINGTHERELEVANTEXPERTISETOBEARFOREXAMPLE,APANELORCOMMITTEEOFPROFESSIONALSANDACADEMICSCOULDBECREATED,ANDCALOHASPROPOSEDTHECREATIONOFAFEDERALROBOTICSCOMMISSIONCALO2014AMACHINEETHICSHOWSHOULDANAUTONOMOUSVEHICLETRADEOFF,SAY,ASMALLPROBABILITYOFINJURYTOAHUMANAGAINSTTHENEARCERTAINTYOFALARGEMATERIALCOSTHOWSHOULDLAWYERS,ETHICISTS,ANDPOLICYMAKERSENGAGETHEPUBLICONTHESEISSUESSHOULDSUCHTRADEOFFSBETHESUBJECTOFNATIONALSTANDARDSAUTONOMOUSWEAPONSCANLETHALAUTONOMOUSWEAPONSBEMADETOCOMPLYWITHHUMANITARIANLAWCHURCHILLANDULFSTEIN2000IF,ASSOMEORGANIZATIONSHAVESUGGESTED,AUTONOMOUSWEAPONSSHOULDBEBANNEDDOCHERTY2012,ISITPOSSIBLETODEVELOPAPRECISEDEFINITIONOFAUTONOMYFORTHISPURPOSE,ANDCANSUCHABANPRACTICALLYBEENFORCEDIFITISPERMISSIBLEORLEGALTOUSELETHALAUTONOMOUSWEAPONS,HOWSHOULDTHESEWEAPONSBEINTEGRATEDINTOTHEEXISTINGCOMMANDANDCONTROLSTRUCTURESOTHATRESPONSIBILITYANDLIABILITYREMAINASSOCIATEDWITHSPECIFICHUMANACTORSWHATTECHNICALREALITIESANDFORECASTSSHOULDINFORMTHESEQUESTIONS,ANDHOWSHOULDMEANINGFULHUMANCONTROLOVERWEAPONSBEDEFINEDROFF2013,2014ANDERSON,REISNER,ANDWAXMAN2014AREAUTONOMOUSWEAPONSLIKELYTOREDUCEPOLITICALAVERSIONTOCONFLICT,ORPERHAPSRESULTINACCIDENTALBATTLESORWARSASARO2008WOULDSUCHWEAPONSBECOMETHETOOLOFCHOICEFOROPPRESSORSORTERRORISTSFINALLY,HOWCANTRANSPARENCYANDPUBLICDISCOURSEBESTBEENCOURAGEDONTHESEISSUESPRIVACYHOWSHOULDTHEABILITYOFAISYSTEMSTOINTERPRETTHEDATAOBTAINEDFROMSURVEILLANCECAMERAS,PHONELINES,EMAILS,ANDSOON,INTERACTWITHTHERIGHTTOPRIVACYHOWWILLPRIVACYRISKSINTERACTWITHCYBERSECURITYANDCYBERWARFARESINGERANDFRIEDMAN2014OURABILITYTOTAKEFULLADVANTAGEOFTHESYNERGYBETWEENAIANDBIGDATAWILLDEPENDINPARTONOURABILITYTOMANAGEANDPRESERVEPRIVACYMANYIKAETAL2011AGRAWALANDSRIKANT2000PROFESSIONALETHICSWHATROLESHOULDCOMPUTERSCIENTISTSPLAYINTHELAWANDETHICSOFAIDEVELOPMENTANDUSEPASTANDCURRENTPROJECTSTOEXPLORETHESEQUESTIONSINCLUDETHEAAAI2008–09PRESIDENTIALPANELONLONGTERMAIFUTURESHORVITZANDSELMAN2009,THEEPSRCPRINCIPLESOFROBOTICSBODENETAL2011,ANDRECENTLYANNOUNCEDPROGRAMSSUCHASSTANFORD’SONEHUNDREDYEARSTUDYOFAIANDTHEAAAICOMMITTEEONAIIMPACTANDETHICALISSUESPOLICYQUESTIONSFROMAPUBLICPOLICYPERSPECTIVE,AILIKEANYPOWERFULNEWTECHNOLOGYENABLESBOTHGREATNEWBENEFITSANDNOVELPITFALLSTOBEAVOIDED,ANDAPPROPRIATEPOLICIESCANENSURETHATWECANENJOYTHEBENEFITSWHILERISKSAREMINIMIZEDTHISRAISESPOLICYQUESTIONSSUCHAS1WHATISTHESPACEOFPOLICIESWORTHSTUDYING,ANDHOWMIGHTTHEYBEENACTED2WHICHCRITERIASHOULDBEUSEDTODETERMINETHEMERITSOFAPOLICYCANDIDATESINCLUDEVERIFIABILITYOFCOM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簡(jiǎn)介：3800英文單詞，英文單詞，21500英文字符，中文英文字符，中文6650字文獻(xiàn)出處文獻(xiàn)出處CHASSIGNOLM,KHOROSHAVINA,KLIMOVAA,ETALARTIFICIALINTELLIGENCETRENDSINEDUCATIONANARRATIVEOVERVIEWJPROCEDIACOMPUTERSCIENCE,2018,1361624ARTIFICIALINTELLIGENCETRENDSINEDUCATIONANARRATIVEOVERVIEWMAUDCHASSIGNOL,ALEKSANDRKHOROSHAVIN,ALEXANDRAKLIMOVA,ANDANNABILYATDINOVAABSTRACTDIGITALTECHNOLOGIESHAVEALREADYBECOMEANINTERNALPARTOFOURLIFETHEYCHANGETHEWAYWEARELOOKINGFORINFORMATION,HOWWECOMMUNICATEWITHEACHOTHER,EVENHOWWEBEHAVETHISTRANSFORMATIONAPPLIESTOMANYAREAS,INCLUDINGEDUCATIONTHEMAINOBJECTIVEOFTHISARTICLEISTOIDENTIFYPROSPECTIVEIMPACTOFARTIFICIALTECHNOLOGIESTOTHESTUDYPROCESSANDTOPREDICTPOSSIBLECHANGESINEDUCATIONALLANDSCAPEINPRESENTEDLITERATUREREVIEWWECONSIDEREDFOURCATEGORIESCUSTOMIZEDEDUCATIONALCONTENT,INNOVATIVETEACHINGMETHODS,TECHNOLOGYENHANCEDASSESSMENT,COMMUNICATIONBETWEENSTUDENTANDLECTURERHAVINGREVIEWEDPUBLICATIONSONTHESUBJECTWEPRESENTHEREAPOSSIBLEPICTUREOFHOWTHEARTIFICIALINTELLIGENCEAIWILLRESHAPEEDUCATIONLANDSCAPEKEYWORDSARTIFICIALINTELLIGENCEEDUCATIONMACHINELEARNINGTECHNOLOGYENHANCEDLEARNING1INTRODUCTIONWEHAVETOADMITTHATDIGITALTECHNOLOGIESHAVEALREADYBECOMEANINTERNALPARTOFOUREVERYDAYLIFETHEYCHANGETHEWAYWEARELOOKINGFORINFORMATION,HOWWECOMMUNICATEWITHEACHOTHER,EVENHOWWEBEHAVEASACONSEQUENCE,THEEDUCATIONALLANDSCAPEHASALSOBEGUNTOCHANGEINDEED,MOREANDMOREEDUCATIONALPROGRAMSINCORPORATEDIGITALCULTUREINTOTHECURRICULUMFOREXAMPLE,INFRANCE,EVENPRIMARYSCHOOLSPROVIDESOMECOURSESABOUTINTERNETTECHNOLOGIES,WHILEHIGHSCHOOLSTUDENTSMUSTPASSANEXAMPROVINGTHEIRCOMPUTERSKILLSMOREOVER,MANYEDUCATIONALFACILITIESHAVELEANINGMANAGEMENTSYSTEMSLMSINSTALLEDSUCHASMOODLE1THESECHANGESAFFECTEDNOTONLYEDUCATIONALCURRICULUMINRECENTYEARSMOREANDMOREDIFFERENTINTERACTIVEEDUCATIONALTECHNOLOGIESAREBECOMINGPOPULARSTUDENTSUSETABLETSINSTEADOFCOPYBOOKS,TEACHERSUTILIZEDIFFERENTLEARNINGPLATFORMSSUCHASGOOGLECLASSROOM,EDMODO,POWERSCHOOL,MOODLETHEREAREALARGENUMBEROFMASSIVEOPENONLINECOURSESMOOCSFORTHEONLINESTUDYSUCHASCOURSERACOMTHEGROWINGAMOUNTOFACTIVATEUSERSOFMOOCSCOURSESSHOWSTHATTHEELECTRONICANDDISTANCELEARNINGMETHODOLOGIESAREAPPRECIATEDBYTHESOCIETYANDSOMEOFTHECOURSESCANGIVESTUDENTSAREALOPPORTUNITYTOGETOFFICIALDEGREEOFSOMEDISTINCTANDVERYRESPECTABLEUNIVERSITYATTHESAMETIME,WECANOBSERVERECENTADVANCESOFVIRTUALREALITYVR,AUGMENTEDREALITYARANDARTIFICIALINTELLIGENCEAIANDITSAPPLICATIONTOEDUCATIONALPROCESSFOREXAMPLE,INNEUROSURGERY,VRTECHNOLOGIESALREADYHAVEASERIOUSIMPACT3DOCULUSSURGICALTHEATERISUSEDFORSIMULATINGSURGERYPROCESSOFREMOVINGBRAINTUMORSFIGURE1MANYAREDUCATIONSPECIFICAPPSCANBEUSEDFORSTUDYINGHIGHLYABSTRACTSUBJECTSARAPPELEMENTS4DISDESIGNEDUNDERSTANDINGATOMICSTRUCTURESOFCHEMICALELEMENTSTHEREAREMANYDEFINITIONSOFAITHATCURRENTLYCOULDBEFOUNDINTHELITERATUREACCORDINGTO2,“ARTIFICIALINTELLIGENCEISTHATACTIVITYDEVOTEDTOMAKINGMACHINESINTELLIGENT,ANDINTELLIGENCEISTHATQUALITYTHATENABLESANENTITYTOFUNCTIONAPPROPRIATELYANDWITHFORESIGHTINITSENVIRONMENT”SOMEANOTHERKEYDEFINITIONOFTHISTECHNOLOGYPRESENTEDIN3AIIS“THEFIELDOFCOMPUTERSCIENCEDEDICATEDTOSOLVINGCOGNITIVEPROBLEMSCOMMONLYKEYWORDSUSEDFORTHESEARCHINGPROCESSWEREASFOLLOWSARTIFICIALINTELLIGENCE,INTELLIGENTTUTORINGSYSTEM,EDUCATION,GAPSINLEARNING,ONLINECLASSROOM,TECHNOLOGYENHANCEDLEARNINGREGARDINGEXCLUSIONANDINCLUSIONCRITERIA,WECONSIDEREDENGLISHLANGUAGEPAPERSPUBLISHEDSINCE2012,PERTINENTTOTHEFOCUSEDPURPOSEOFTHESTUDY22DESCRIPTIONOFMODELFRAMEWORKFORANARRATIVEOVERVIEWINORDERTOMAKEANADEQUATEPRESENTATIONOFTHELITERATUREFINDINGS,WEPROPOSETHEFOLLOWINGMODELFRAMEWORKOFTHEEDUCATIONALLANDSCAPETHISMODELISPRESENTEDINFIGURE1WECONSIDERFOURMAJORPARTSOFTHEEDUCATIONALPROCESSTHATCOULDBEAFFECTEDBYAICONTENTTEACHINGMETHODSASSESSMENTCOMMUNICATIONTERMCONTENTREFERSTOTHEBODYOFKNOWLEDGEANDINFORMATIONTHATTEACHERSTEACHANDTHATSTUDENTSAREEXPECTEDTOLEARNINAGIVENSUBJECTORCONTENTAREAINTHISPAPER,WECONSIDERTHATITMAYINCLUDEBOTHEDUCATIONALCONTENTANDITSCUSTOMIZATIONTEACHINGMETHODSREPRESENTDIFFERENTPRINCIPLESANDMETHODSUSEDBYTEACHERSTOENABLESTUDENTLEARNINGTHESESTRATEGIESAREDETERMINEDPARTLYONTHESUBJECTMATTERTOBETAUGHTANDPARTLYBYTHENATUREOFTHELEARNERTHISPARTISVERYINTERESTINGANDIMPORTANTASNAMELYTEACHINGMETHODSARECURRENTLYAFFECTEDBYNEWTECHNOLOGIESASSESSMENTREFERSTOTHEWIDEVARIETYOFMETHODSORTOOLSTHATEDUCATORSUSETOEVALUATE,MEASURE,ANDDOCUMENTTHEACADEMICREADINESS,LEARNINGPROGRESS,SKILLACQUISITION,OREDUCATIONALNEEDSOFSTUDENTSWITHTHEDEVELOPMENTOFMOOCS,THEREISANINCREASINGNECESSITYWITHTECHNOLOGYENHANCEDASSESSMENTTOOLSTHOSETHREEPARTSJOINDIFFERENTELEMENTSOFTHELEARNINGPROCESSWEALSOADDEDTHERECOMMUNICATIONPARTASESSENTIALFORSTUDENTTEACHERINTERACTIONITISALSOREFERREDTOMOOCS,TRADITIONALCLASSESWITHMANYSTUDENTSANDMULTIDISCIPLINARYCOURSESFIGURE1MODELFRAMEWORKTHEFOLLOWINGSECTIONOFTHEPAPERPRESENTRESULTSANDDISCUSSIONOFFINDINGSINACCORDANCEWITHTHEFRAMEWORKDESCRIBED3TRENDSANDOPPORTUNITIES

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簡(jiǎn)介：人工智能導(dǎo)論人工智能導(dǎo)論課程論文課程論文題目目人工智能導(dǎo)論課程論文專業(yè)業(yè)計(jì)算機(jī)科學(xué)與技術(shù)班級(jí)級(jí)N計(jì)科121F姓名名吳文定學(xué)號(hào)號(hào)24122401811指導(dǎo)老師指導(dǎo)老師白天人工智能結(jié)課報(bào)告3前言前言人工智能是經(jīng)過40多年發(fā)展起來的一門綜合性學(xué)科，它旨在研究如何利用計(jì)算機(jī)等現(xiàn)代工具設(shè)計(jì)模擬人類智能行為的系統(tǒng)。在眾多的人工智能應(yīng)用領(lǐng)域中，專家系統(tǒng)是30多年來發(fā)展起來的一種最具代表性的智能應(yīng)用系統(tǒng)，它旨在研究如何設(shè)計(jì)基于知識(shí)的計(jì)算機(jī)程序系統(tǒng)來模擬人類專家求解專門問題的能力。專家系統(tǒng)是人工智能中最活躍的一個(gè)分支，是人工智能發(fā)展最重要的推動(dòng)力。由于人類對(duì)自身的思維規(guī)律和智能行為仍在探索中，因此，人工智能與專家系統(tǒng)仍然是一門開放的年輕學(xué)科。近幾年來，人工智能與專家系統(tǒng)的研究越來越深入，新的思想、新的理論以及新的方法與技術(shù)不斷涌現(xiàn)，新的研究成果不斷充實(shí)著這一研究領(lǐng)域，尤其是模糊邏輯與神經(jīng)網(wǎng)絡(luò)及其結(jié)合的研究已成為當(dāng)前人工智能或智能模擬的重要研究方向，學(xué)術(shù)論文數(shù)以千計(jì)，應(yīng)用成果迭出。

簡(jiǎn)介：0附件四附件四英文文獻(xiàn)原文英文文獻(xiàn)原文ARTIFICIALARTIFICIALINTELLIGENCEINTELLIGENCE“ARTIFICIALINTELLIGENCE“ISAWORDWASORIGINALLYDARTMOUTHIN1956TOPUTFORWARDFROMTHENON,RESEARCHERSHAVEDEVELOPEDMANYTHEORIESANDPRINCIPLES,THECONCEPTOFARTIFICIALINTELLIGENCEISALSOEXPANDSARTIFICIALINTELLIGENCEISACHALLENGINGJOBOFSCIENCE,THEPERSONMUSTKNOWCOMPUTERKNOWLEDGE,PSYCHOLOGYANDPHILOSOPHYARTIFICIALINTELLIGENCEISINCLUDEDAWIDERANGEOFSCIENCE,ITISCOMPOSEDOFDIFFERENTFIELDS,SUCHASMACHINELEARNING,COMPUTERVISION,ETC,ONTHEWHOLE,THERESEARCHONARTIFICIALINTELLIGENCEISONEOFTHEMAINGOALSOFTHEMACHINECANDOSOMEUSUALLYNEEDTOPERFORMCOMPLEXHUMANINTELLIGENCEBUTINDIFFERENTTIMESANDDIFFERENTPEOPLEINTHE“COMPLEX“UNDERSTANDINGISDIFFERENTSUCHASHEAVYSCIENCEANDENGINEERINGCALCULATIONWASSUPPOSEDTOBETHEBRAINTOUNDERTAKE,NOWCOMPUTERCANNOTONLYCOMPLETETHISCALCULATION,ANDFASTERTHANTHEHUMANBRAINCANMOREACCURATELY,ANDTHUSTHEPEOPLENOLONGERPUTTHISCALCULATIONISREGARDEDAS“THENEEDTOPERFORMCOMPLEXHUMANINTELLIGENCE,COMPLEXTASKS“WORKISDEFINEDASTHEDEVELOPMENTOFTHETIMESANDTHEPROGRESSOFTECHNOLOGY,ARTIFICIALINTELLIGENCEISTHESCIENCEOFSPECIFICTARGETANDNATUREASTHETIMESCHANGEANDDEVELOPMENTONTHEONEHANDITCONTINUESTOGAINNEWPROGRESSONTHEONEHAND,ANDTURNINGTOMOREMEANINGFUL,THEMOREDIFFICULTTHETARGETCURRENTCANBEUSEDTOSTUDYTHEMAINMATERIALOFARTIFICIALINTELLIGENCEANDARTIFICIALINTELLIGENCETECHNOLOGYTOREALIZETHEMACHINEISACOMPUTER,THEDEVELOPMENTHISTORYOFARTIFICIALINTELLIGENCEISCOMPUTERSCIENCEANDTECHNOLOGYANDTHEDEVELOPMENTTOGETHERBESIDESTHECOMPUTERSCIENCEANDARTIFICIALINTELLIGENCEALSOINVOLVESINFORMATION,CYBERNETICS,AUTOMATION,BIONICS,BIOLOGY,PSYCHOLOGY,LOGIC,LINGUISTICS,MEDICINEANDPHILOSOPHYANDMULTIDISCIPLINEARTIFICIALINTELLIGENCERESEARCHINCLUDEKNOWLEDGEREPRESENTATION,AUTOMATICREASONINGANDSEARCHMETHOD,MACHINELEARNINGANDKNOWLEDGEACQUISITIONANDPROCESSINGOFKNOWLEDGESYSTEM,NATURALLANGUAGEPROCESSING,COMPUTERVISION,INTELLIGENTROBOT,AUTOMATICPROGRAMDESIGN,ETCPRACTICALAPPLICATIONOFMACHINEVISIONFINGERPRINTIDENTIFICATION,2EXTENSIVEATTENTIONANDINTHEROBOT,ECONOMICANDPOLITICALDECISIONS,CONTROLSYSTEM,SIMULATIONSYSTEMAPPLICATIONINOTHERAREAS,ITALSOPLAYEDANINDISPENSABLEROLETHEFAMOUSAMERICANSTANFORDUNIVERSITYPROFESSORNELSONARTIFICIALINTELLIGENCERESEARCHCENTEROFARTIFICIALINTELLIGENCEUNDERSUCHADEFINITION“ARTIFICIALINTELLIGENCEABOUTTHEKNOWLEDGEOFTHESUBJECTISANDHOWTOREPRESENTKNOWLEDGEHOWTOGAINKNOWLEDGEANDUSEOFSCIENTIFICKNOWLEDGEBUTANOTHERAMERICANMITPROFESSORWINSTONTHOUGHT“ARTIFICIALINTELLIGENCEISHOWTOMAKETHECOMPUTERTODOWHATONLYCANDOINTELLIGENTWORK“THESECOMMENTSREFLECTTHEARTIFICIALINTELLIGENCEDISCIPLINEBASICIDEASANDBASICCONTENTNAMELYARTIFICIALINTELLIGENCEISTHESTUDYOFHUMANINTELLIGENCEACTIVITIES,HASCERTAINLAW,RESEARCHOFARTIFICIALINTELLIGENCESYSTEM,HOWTOMAKETHECOMPUTERTOCOMPLETEBEFORETHEINTELLIGENCENEEDSTODOWORK,ALSOISTOSTUDYHOWTHEAPPLICATIONOFCOMPUTERHARDWAREANDSOFTWARETOSIMULATEHUMANSOMEINTELLIGENTBEHAVIOROFTHEBASICTHEORY,METHODSANDTECHNIQUESARTIFICIALINTELLIGENCEISABRANCHOFCOMPUTERSCIENCE,SINCETHE1970S,KNOWNASONEOFTHETHREETECHNOLOGIESSPACETECHNOLOGY,ENERGYTECHNOLOGY,ARTIFICIALINTELLIGENCEALSOCONSIDEREDTHE21STCENTURYGENETICENGINEERING,NANOSCIENCE,ARTIFICIALINTELLIGENCEISONEOFTHETHREETECHNOLOGIESITISNEARLYTHREEYEARSITHASBEENDEVELOPEDRAPIDLY,ANDINMANYFIELDSAREWIDELYAPPLIED,ANDHAVEMADEGREATACHIEVEMENTS,ARTIFICIALINTELLIGENCEHASGRADUALLYBECOMEANINDEPENDENTBRANCH,BOTHINTHEORYANDPRACTICEAREALREADYBECOMESASYSTEMITSRESEARCHRESULTSAREGRADUALLYINTEGRATEDINTOPEOPLESLIVES,ANDCREATEMOREHAPPINESSFORMANKINDARTIFICIALINTELLIGENCEISTHATTHECOMPUTERSIMULATIONRESEARCHOFSOMETHINKINGPROCESSANDINTELLIGENTBEHAVIORSUCHASSTUDY,REASONING,THINKING,PLANNING,ETC,INCLUDINGCOMPUTERTOREALIZEINTELLIGENTPRINCIPLE,MAKESIMILARTOTHATOFHUMANINTELLIGENCE,COMPUTERCANACHIEVEHIGHERLEVELOFCOMPUTERAPPLICATIONARTIFICIALINTELLIGENCEWILLINVOLVETHECOMPUTERSCIENCE,PHILOSOPHYANDLINGUISTICS,PSYCHOLOGY,ETCTHATWASALMOSTNATURALSCIENCEANDSOCIALSCIENCEDISCIPLINES,THESCOPEOFALLALREADYFARBEYONDTHESCOPEOFCOMPUTERSCIENCEANDARTIFICIALINTELLIGENCEANDTHINKINGSCIENCEISTHERELATIONSHIPBETWEENTHEORYANDPRACTICE,ARTIFICIALINTELLIGENCEISINTHEMODEOFTHINKINGSCIENCETECHNOLOGYAPPLICATIONLEVEL,ISONEOFITSAPPLICATIONFROMTHEVIEWOFTHINKING,ARTIFICIALINTELLIGENCEISNOT

簡(jiǎn)介：什么是模式什么是模式模式具體事物所具有的信息。對(duì)象之間存在的規(guī)律性關(guān)系。存在于時(shí)間和空間中可觀察的事物，如果可以區(qū)別它們是否相同或是否相似，都可稱之為模式。模式是指我們從事物獲得的信息，往往表現(xiàn)為具有時(shí)間或空間分布的信息。模式識(shí)別的作用和目的就是在面對(duì)某一具體的事物時(shí)將其正確歸入某一類別。模式識(shí)別的含義模式識(shí)別的含義模式識(shí)別是研究用計(jì)算機(jī)來實(shí)現(xiàn)人類識(shí)別模式的能力用一定數(shù)量的樣本（訓(xùn)練集或?qū)W習(xí)集）進(jìn)行分類器的設(shè)計(jì)，用所設(shè)計(jì)的分類器對(duì)待識(shí)別的樣本進(jìn)行分類決策。模式識(shí)別與人工智能的區(qū)別模式識(shí)別與人工智能的區(qū)別模式識(shí)別是人工智能應(yīng)用的一個(gè)方面。模式識(shí)別是一個(gè)不斷發(fā)展的新學(xué)科,它的理論基礎(chǔ)和研究范圍也在不斷發(fā)展,隨著應(yīng)用范圍的不斷擴(kuò)大以及計(jì)算機(jī)科學(xué)的不斷進(jìn)步,基于人工神經(jīng)網(wǎng)絡(luò)的模式識(shí)別技術(shù)在今后將會(huì)得到更大的發(fā)展,量子計(jì)算技術(shù)也將用于模式識(shí)別研究。人工智能下包括人工智能理論，模式識(shí)別，神經(jīng)網(wǎng)絡(luò)，自然語言處理，專家系統(tǒng)等等多個(gè)方面。模式識(shí)別系統(tǒng)由哪幾個(gè)部分組成模式識(shí)別系統(tǒng)由哪幾個(gè)部分組成基于統(tǒng)計(jì)方法的模式識(shí)別系統(tǒng)主要有4個(gè)部分組成數(shù)據(jù)獲取，預(yù)處理，特征提取和選擇，分類決策。數(shù)據(jù)獲取包括一維波形、二維圖像、物理參量和邏輯值等。預(yù)處理除去噪聲，加強(qiáng)有用信息，并對(duì)測(cè)量?jī)x器或其它因素造成的退化現(xiàn)象進(jìn)行復(fù)原。特征提取和選擇由于圖像或波形所獲得的數(shù)據(jù)量相當(dāng)大，為了有效的實(shí)現(xiàn)分類識(shí)別，就要對(duì)原始數(shù)據(jù)進(jìn)行變換，得到最能反映分類本質(zhì)的特征。分類決策在特征空間中用統(tǒng)計(jì)方法把被識(shí)別對(duì)象歸為某一類別。假如只知道先驗(yàn)概率，用哪種決策規(guī)則假如只知道先驗(yàn)概率，用哪種決策規(guī)則設(shè)一個(gè)有C類，每一類的先驗(yàn)概率為PWJ，J1,,C。此時(shí)最小錯(cuò)誤率貝葉斯決策規(guī)則為如果PWIMAXPWJ，則X∈WI。假如只知道后驗(yàn)概率，用哪種決策規(guī)則假如只知道后驗(yàn)概率，用哪種決策規(guī)則設(shè)一個(gè)有C類，每一類的后驗(yàn)概率為PWJ|X，J1,,C。此時(shí)最小錯(cuò)誤率貝葉斯決策規(guī)則為如果PWI|XMAXPWJ|X，則X∈WI。貝葉斯決策理論的含義貝葉斯決策理論的含義貝葉斯決策利用先驗(yàn)概率和類條件概率密度，將貝葉斯公式（加上貝葉斯公式）作為理論依據(jù)，對(duì)某一樣本按其特征向量進(jìn)行分類。貝葉斯決策的先決條件貝葉斯決策的先決條件（1）各類別總體的概率分布是已知的。（2）要決策分類的類別數(shù)是一定的。（1）物理上的合理性（2）數(shù)學(xué)上比較簡(jiǎn)便什么是監(jiān)督參數(shù)估計(jì)什么是監(jiān)督參數(shù)估計(jì)監(jiān)督參數(shù)估計(jì)樣本所屬類別及類條件總體概率密度函數(shù)的形式已知，某些參數(shù)未知。非監(jiān)督參數(shù)估計(jì)已知總體概率密度函數(shù)形式，但未知樣本類別,要推斷某些參數(shù)。非參數(shù)估計(jì)已知樣本類別，未知總體概率密度函數(shù)形式，要求直接推斷概率密度函數(shù)本身。非監(jiān)督參數(shù)估計(jì)的方法有哪些非監(jiān)督參數(shù)估計(jì)的方法有哪些迭代法非參數(shù)估計(jì)的方法有哪些非參數(shù)估計(jì)的方法有哪些PARZEN窗估計(jì)方法和K近鄰概率密度估計(jì)方法。PARZEN窗估計(jì)方法的主題思想是固定窗口區(qū)域容積，去看有多少個(gè)樣本點(diǎn)在里面，而K近鄰概率密度估計(jì)方法的主要思想是固定樣本點(diǎn)的個(gè)數(shù)（K個(gè)）看需要的多大的容積。最大似然估計(jì)和貝葉斯估計(jì)的差異最大似然估計(jì)和貝葉斯估計(jì)的差異最大似然估計(jì)是把參數(shù)Θ看成為確定的未知參數(shù)。貝葉斯估計(jì)是把參數(shù)Θ看成隨機(jī)的未知參數(shù)。什么情況下使用最大似然估計(jì)什么情況下使用最大似然估計(jì)適用于參數(shù)是確定的的情況。什么情況下使用貝葉斯估計(jì)什么情況下使用貝葉斯估計(jì)適用于參數(shù)是隨機(jī)的的情況。什么是可識(shí)別性問題什么是可識(shí)別性問題從混合密度中把Θ的分量恢復(fù)出來。設(shè)Θ≠Θ，如果對(duì)于混合分布中的每個(gè)X都有PX|Θ≠PX|Θ，則稱密度PX|Θ是可識(shí)別的。為什么用線性判別函數(shù)為什么用線性判別函數(shù)簡(jiǎn)單、易實(shí)現(xiàn)，計(jì)算和存儲(chǔ)量小。FISHER線性判別函數(shù)的含義線性判別函數(shù)的含義考慮把維空間的樣本投影到一條直線上，形成一維空間，即把維數(shù)壓縮到一維。在一般的情況下，（對(duì)于投影）總可以找到某個(gè)方向，使在這個(gè)方向的直線上樣本的投影能分開得好。線性判別函數(shù)不滿足要求時(shí)，用什么樣的方法來判別線性判別函數(shù)不滿足要求時(shí)，用什么樣的方法來判別廣義判別函數(shù)。將非線性函數(shù)，通過映射，變成“線性”函數(shù)。什么是分段線性判別函數(shù)什么是分段線性判別函數(shù)實(shí)際中有很多復(fù)雜的模式識(shí)別問題并不是線性可分的，簡(jiǎn)單的線性判別函數(shù)往往會(huì)帶來較大的分類錯(cuò)誤，這時(shí)就需要采用非線性分類器。分段線性判別函數(shù)是一種特殊的非線性分

簡(jiǎn)介：中國(guó)人工智能系列白皮書中國(guó)人工智能系列白皮書中國(guó)人工智能系列白皮書智能農(nóng)業(yè)智能農(nóng)業(yè)中國(guó)人工智能學(xué)會(huì)中國(guó)人工智能學(xué)會(huì)二○一六年九月一六年九月中國(guó)人工智能系列白皮書目錄第1章智能農(nóng)業(yè)發(fā)展背景111人工智能在農(nóng)業(yè)領(lǐng)域中的應(yīng)用歷程112智能農(nóng)業(yè)及其發(fā)展趨勢(shì)8第2章農(nóng)業(yè)智能分析1221農(nóng)業(yè)數(shù)據(jù)挖掘12211農(nóng)業(yè)數(shù)據(jù)挖掘特點(diǎn)12212農(nóng)業(yè)網(wǎng)絡(luò)數(shù)據(jù)挖掘13213農(nóng)業(yè)數(shù)據(jù)挖掘應(yīng)用1622農(nóng)業(yè)數(shù)據(jù)語義分析18221農(nóng)業(yè)數(shù)據(jù)語義模型18222農(nóng)業(yè)數(shù)據(jù)存儲(chǔ)模型19223農(nóng)業(yè)數(shù)據(jù)知識(shí)發(fā)現(xiàn)20224農(nóng)業(yè)數(shù)據(jù)語義檢索21225分布式農(nóng)業(yè)知識(shí)協(xié)同構(gòu)建2123農(nóng)業(yè)病蟲害圖像識(shí)別22231基于機(jī)器視覺的農(nóng)業(yè)病蟲害自動(dòng)監(jiān)測(cè)識(shí)別系統(tǒng)框架23232農(nóng)業(yè)病蟲害圖像采集方法24233農(nóng)業(yè)病蟲害圖像預(yù)處理26234農(nóng)業(yè)病蟲害特征提取與識(shí)別模型構(gòu)建27235農(nóng)業(yè)病蟲害模式識(shí)別2824動(dòng)物行為分析2925農(nóng)產(chǎn)品無損檢測(cè)34251農(nóng)產(chǎn)品的無損檢測(cè)35252農(nóng)產(chǎn)品無損檢測(cè)主要方法與基本原理36253無損檢測(cè)在農(nóng)產(chǎn)品質(zhì)量檢測(cè)中的應(yīng)用381

簡(jiǎn)介：人工智能學(xué)習(xí)心得人工智能學(xué)習(xí)心得第一篇人工智能學(xué)習(xí)心得人工智能學(xué)習(xí)心得對(duì)人工智能的理解通過這學(xué)期的學(xué)習(xí)，我對(duì)人工智能有了一定的感性認(rèn)識(shí)，個(gè)人覺得人工智能是一門極富挑戰(zhàn)性的科學(xué)，從事這項(xiàng)工作的人必須懂得計(jì)算機(jī)知識(shí)，心理學(xué)和哲學(xué)。人工智能是包括十分廣泛的科學(xué)，它由不同的領(lǐng)域組成，如機(jī)器學(xué)習(xí)，計(jì)算機(jī)視覺等等，總的說來，人工智能研究的一個(gè)主要目標(biāo)是使機(jī)器能夠勝任一些通常需要人類智能才能完成的復(fù)雜工作。人工智能的定義可以分為兩部分，即“人工”和“智能”。“人工”比較好理解，爭(zhēng)議性也不大。有時(shí)我們會(huì)要考慮什么是人力所能及制造的，或者人自身的智能程度有沒有高到可以創(chuàng)造人工智能的地步，等等。但總的來說，“人工系統(tǒng)”就是通常意義下的人工系統(tǒng)。關(guān)于什么是“智能”，就問題多多了。這涉及到其它諸如意識(shí)、自我、思維等等問題。人唯一了解的智能是人本身的智能，這是普遍認(rèn)同的觀點(diǎn)。但是我們對(duì)我們自身智能的理解都非常有限，對(duì)構(gòu)成人的智能的必要元素也了解有限，所以就很難定義什么是“人工”制造的“智能”了。關(guān)于人工智能一個(gè)大家比較容易接受的定義是這樣的人工智能是人造的智能,是計(jì)算機(jī)科學(xué)、邏輯學(xué)、認(rèn)知科學(xué)交叉形成的一門科學(xué)，簡(jiǎn)稱AI。人工智能的發(fā)展歷史大致可以分為這幾個(gè)階段第一階段50年代人工智能的興起和冷落目標(biāo)問題求解，將人工智能更面向?qū)嵱谩Ａ硗?，由于HOPFIELD多層神經(jīng)網(wǎng)絡(luò)模型的提出，使人工神經(jīng)網(wǎng)絡(luò)研究與應(yīng)用出現(xiàn)了欣欣向榮的景象。人工智能已深入到社會(huì)生活的各個(gè)領(lǐng)域。對(duì)人工智能對(duì)世界的影響的感受及未來暢想最近看了電影黑客帝國(guó)一系列，對(duì)其中的科幻生活有了很大的興趣，不覺有了疑問現(xiàn)在的世界是否會(huì)如電影中一樣呢人工智能的神話是否會(huì)發(fā)生在當(dāng)前社會(huì)中的呢在黑客帝國(guó)的世界里，程序員成為了耶穌，控制著整個(gè)世界，黑客帝國(guó)之所以成為經(jīng)典，我認(rèn)為，不是因?yàn)轱w來飛去的超級(jí)人物，而是因?yàn)樗底越沂玖艘粋€(gè)人與計(jì)算機(jī)世界的關(guān)系，一個(gè)發(fā)展趨勢(shì)。誰知道200年以后會(huì)不會(huì)是智能機(jī)器統(tǒng)治了世界人類正向信息化的時(shí)代邁進(jìn)，信息化是當(dāng)前時(shí)代的主旋律。信息抽象結(jié)晶為知識(shí)，知識(shí)構(gòu)成智能的基礎(chǔ)。因此，信息化到知識(shí)化再到智能化，必將成為人類社會(huì)發(fā)展的趨勢(shì)。人工智能已經(jīng)并且廣泛而有深入的結(jié)合到科學(xué)技術(shù)的各門學(xué)科和社會(huì)的各個(gè)領(lǐng)域中，她的概念，方法和技術(shù)正在各行各業(yè)廣泛滲透。而在我們的身邊，智能化的例子也屢見不鮮。在軍事、工業(yè)和醫(yī)學(xué)等領(lǐng)域中人工智能的應(yīng)用已經(jīng)顯示出了它具有明顯的經(jīng)濟(jì)效益潛力，和提升人們生活水平的最大便利性和先進(jìn)性。智能是一個(gè)寬泛的概念。智能是人類具有的特征之一。然而，對(duì)于什么是人類智能（或者說智力），科學(xué)界至今還沒有給出令人滿意

簡(jiǎn)介：PREPARINGFORTHEFUTUREOFARTIFICIALINTELLIGENCENATIONALSCIENCEANDTECHNOLOGYCOUNCILPREPARINGFORTHEFUTUREOFARTIFICIALINTELLIGENCEEXECUTIVEOFFICEOFTHEPRESIDENTNATIONALSCIENCEANDTECHNOLOGYCOUNCILCOMMITTEEONTECHNOLOGYOCTOBER2016ABOUTTHENATIONALSCIENCEANDTECHNOLOGYCOUNCILTHENATIONALSCIENCEANDTECHNOLOGYCOUNCILNSTCISTHEPRINCIPALMEANSBYWHICHTHEEXECUTIVEBRANCHCOORDINATESSCIENCEANDTECHNOLOGYPOLICYACROSSTHEDIVERSEENTITIESTHATMAKEUPTHEFEDERALRESEARCHANDDEVELOPMENTRHOMELANDANDNATIONALSECURITYSCIENCE,TECHNOLOGY,ENGINEERING,ANDMATHEMATICSSTEMEDUCATIONSCIENCEANDTECHNOLOGYEACHOFTHESECOMMITTEESOVERSEESSUBCOMMITTEESANDWORKINGGROUPSTHATAREFOCUSEDONDIFFERENTASPECTSOFSCIENCEANDTECHNOLOGYMOREINFORMATIONISAVAILABLEATWWWWHITEHOUSEGOV/OSTP/NSTCABOUTTHEOFFICEOFSCIENCEANDTECHNOLOGYPOLICYTHEOFFICEOFSCIENCEANDTECHNOLOGYPOLICYOSTPWASESTABLISHEDBYTHENATIONALSCIENCEANDTECHNOLOGYPOLICY,ORGANIZATION,ANDPRIORITIESACTOF1976OSTP’SRESPONSIBILITIESINCLUDEADVISINGTHEPRESIDENTINPOLICYFORMULATIONANDBUDGETDEVELOPMENTONQUESTIONSINWHICHSCIENCEANDTECHNOLOGYAREIMPORTANTELEMENTSARTICULATINGTHEPRESIDENT’SSCIENCEANDTECHNOLOGYPOLICYANDPROGRAMSANDFOSTERINGSTRONGPARTNERSHIPSAMONGFEDERAL,STATE,ANDLOCALGOVERNMENTS,ANDTHESCIENTIFICCOMMUNITIESININDUSTRYANDACADEMIATHEDIRECTOROFOSTPALSOSERVESASASSISTANTTOTHEPRESIDENTFORSCIENCEANDTECHNOLOGYANDMANAGESTHENSTCMOREINFORMATIONISAVAILABLEATWWWWHITEHOUSEGOV/OSTPACKNOWLEDGMENTSTHISDOCUMENTWASDEVELOPEDTHROUGHTHECONTRIBUTIONSOFSTAFFFROMOSTP,OTHERCOMPONENTSOFTHEEXECUTIVEOFFICEOFTHEPRESIDENT,ANDOTHERDEPARTMENTSANDAGENCIESASPECIALTHANKSANDAPPRECIATIONTOEVERYONEWHOCONTRIBUTEDCOPYRIGHTINFORMATIONTHISISAWORKOFTHEUSGOVERNMENTANDISINTHEPUBLICDOMAINITMAYBEFREELYDISTRIBUTED,COPIED,ANDTRANSLATEDACKNOWLEDGMENTOFPUBLICATIONBYTHEOFFICEOFSCIENCEANDTECHNOLOGYPOLICYISAPPRECIATEDANYTRANSLATIONSHOULDINCLUDEADISCLAIMERTHATTHEACCURACYOFTHETRANSLATIONISTHERESPONSIBILITYOFTHETRANSLATORANDNOTOSTPITISREQUESTEDTHATACOPYOFANYTRANSLATIONBESENTTOOSTPTHISWORKISAVAILABLEFORWORLDWIDEUSEANDREUSEANDUNDERTHECREATIVECOMMONSCC010UNIVERSALLICENSE