{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","title":"人工智能哲学","author":null,"edition":null,"publisher":null,"year":null,"isbn":"7532740544","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","id":"7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","uuid":"7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","title":"人工智能哲学","normalized_title":"人工智能哲学","author":null,"edition":null,"publisher":null,"year":null,"isbn":"7532740544","isbns":["7532740544"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":501,"navigation_url":"https://workshop.closeclaw.top/ai/book/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E5%93%B2%E5%AD%A6","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2","page_url":"https://workshop.closeclaw.top/api/ai/books/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2/page","search_url":"https://workshop.closeclaw.top/api/ai/books/7f418071-0fdc-4a5a-a4c5-82dd1979d9c2/search"},"page":{"printed_page":19,"pdf_page":27,"physical_index":27,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"82760103b6bd1d0da41601928b5d541264b0f5594efed9da10905c2f302ec0a1"},"chapter":"人工智能哲学","content":"H·德雷福斯和S·德雷福斯在“造就心灵还是建立大脑模型：人工智能的分歧点”一文(第13章)中承认，对于那些耳熟能详的批评，联结论可以在一定程度上为AI作出辩护。但是他们仍然反对海斯和克拉克的观点，坚持认为，语言和常识不可能为AI所获取(即使是联结论类的也不行）。在捍卫这一立场时，德雷福斯把AI研究同内容广泛的哲学文献联系起来，比较了西方理性主义传统同大陆的现象学和后期维特根斯坦的不同特点。他对AI的怀疑源于这样的观点：人们并不使用关于日常世界的理论，科学也不能表达这样的理论，因为并不存在一组与语境无关的理解原素。我们的知识是熟练的技能，不同于过程规则，表述方式或知识内容，甚至我们关于形式系统的知识也不能不借助干有关怎样延续数学序列或应用逻辑规则的背景直觉。\n\n德雷福斯在概述AI两个分支激烈对抗的历史(但略去了作为这两个分支共同来源的麦卡洛克和皮茨的工作)时谈到神经网络研究的早期成就和暂时沉寂，形式主义AI的初始成功，以及继之而来的、对常识性理解编程时遇到的困难。特别是，传统AI不能获得整体知觉、语境敏感性和对族的相似性及相关性的识别而这每一方面在联结论中都得到了较好的处理。德雷福斯对AI前20年评价是“理性主义传统终于被置于经验检验之下，而它失败了”。德雷福斯认为联结论是对他这一观点的支持：智能并不依赖于关于世界的理论，所以不能在计算系统中通过规则来获取，或作出模型(Dreyfus1979)。\n\n导 言\n\n19","previous_page":18,"next_page":20}