{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"72c4da97-7cf2-441a-a985-c1252297d6a3","title":"人工智能的进化 计算机思维离人类心智还有多远","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787508685670","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"72c4da97-7cf2-441a-a985-c1252297d6a3","id":"72c4da97-7cf2-441a-a985-c1252297d6a3","uuid":"72c4da97-7cf2-441a-a985-c1252297d6a3","title":"人工智能的进化 计算机思维离人类心智还有多远","normalized_title":"人工智能的进化计算机思维离人类心智还有多远","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787508685670","isbns":["9787508685670"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":216,"navigation_url":"https://workshop.closeclaw.top/ai/book/72c4da97-7cf2-441a-a985-c1252297d6a3","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E7%9A%84%E8%BF%9B%E5%8C%96%20%E8%AE%A1%E7%AE%97%E6%9C%BA%E6%80%9D%E7%BB%B4%E7%A6%BB%E4%BA%BA%E7%B1%BB%E5%BF%83%E6%99%BA%E8%BF%98%E6%9C%89%E5%A4%9A%E8%BF%9C","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/72c4da97-7cf2-441a-a985-c1252297d6a3/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/72c4da97-7cf2-441a-a985-c1252297d6a3/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/72c4da97-7cf2-441a-a985-c1252297d6a3","page_url":"https://workshop.closeclaw.top/api/ai/books/72c4da97-7cf2-441a-a985-c1252297d6a3/page","search_url":"https://workshop.closeclaw.top/api/ai/books/72c4da97-7cf2-441a-a985-c1252297d6a3/search"},"page":{"printed_page":188,"pdf_page":199,"physical_index":199,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"d741066389086d2cf444c5f2674bea9c3c3b88b7e4c8a3677e5ab58d4ad54184"},"chapter":"第9章 基于知识的系统","content":"知识表示假说引自布莱恩·史密斯（Brian Smith）的博士论文(Reflection and Semantics in a Procedural Language )。 人们通常会将此观点归功于约翰·麦卡锡，但是显而易见，其他研究人员与他的观点很相似。对于艾伦·纽厄尔（AllenNewell）和赫伯·西蒙（HerbSimon）而言，重点更多放在象征领域，因此他们的版本被称为物理符号系统假说（physical symbol system hypothesis),他们认为:“物理符号系统是普遍智能行为的充分必要条件”(见Computer Science as empirical inquiry: Symbols and search)。( 马文·明斯基作为早期人工智能的研究人员之一，他发现了逻辑和数值方法对于人工智能都有很大局限，提出应将这些方法进行融合，可参见Logical versus symbolic versus connectionist or neatversus scruffy。)\n\nKnowledge Representation and Reasoning 和 KnowledgeRepresentation, Reasoning and Declarative Problem solving 这 两本书专门介绍了人工智能中的知识表示和推理领域。此外，还有每两年举行一次的该领域的学术会议（见http://kr.org)。可以在Readings in knowledge Representation中找到相关的早期内容。Logical Foundations of Artificial Intelligence 和ComputationalIntelligence: A Logical Approach提出了逻辑是人工智能统一的主题, The role of logic in knowledge representation and common sensereasoning 和 The role of gic in knowledge representation 对此进行了进一步讨论。马文·明斯基关于逻辑的论述摘自Aframeworkfor representing knowledge 第 262 页。Logic, probability and humanreasoning是从心理学方面看待推理。关于根据信仰程度不同，用概率的方法进行推理的优势，可参见 Bayesian Rationality: TheProbabilistic Approach to Human Reasoning\n\n人工智能的进化\n\n188","previous_page":187,"next_page":189}