{"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":32,"pdf_page":40,"physical_index":40,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"921b4f89a773eb86f3f153c2ed4094272c010fbd33bd089b36da6f4ba61104ac"},"chapter":"人工智能哲学","content":"图1-1 图中的表达式。图中神经元ci始终以细胞体上的数字i来标记，而对 $c _ { i }$ 应动作则和正文中一样由带有下标i的 $\" N \"$ 来表示。\n\na. ${ \\cal N } _ { 2 } ( t ) . \\equiv . { \\cal N } _ { 1 } ( t ^ { - 1 } )$\n\nb. ${ \\cal N } _ { 3 } ( t ) . \\equiv . { \\cal N } _ { 1 } ( t - 1 ) \\vee { \\cal N } _ { 2 } ( t - 1 )$\n\n${ \\cal N } _ { 3 } ( t ) . \\equiv . { \\cal N } _ { 1 } ( t - 1 ) . { \\cal N } _ { 2 } ( t - 1 )$ C.\n\nd. ${ \\cal N } _ { 3 } ( t ) , \\equiv . { \\cal N } _ { 1 } ( t - 1 ) . \\sim { \\cal N } _ { 2 } ( t - 1 )$\n\ne. $\\tilde { N _ { 3 } } ( t ) _ { ! } \\equiv _ { ! } N _ { 1 } ( t - 1 ) . \\vee . N _ { 2 } ( t - 3 ) . \\sim N _ { 2 } ( t - 2 )$\n\n$$\n{ \\cal N } _ { 4 } ( t ) . \\equiv . { \\cal N } _ { 2 } ( t - 2 ) . { \\cal N } _ { 2 } ( t - 1 )\n$$\n\nf. $\\begin{array} { r l } & { \\mathrm { ~ \\ } _ { N 4 } ^ { n } ( t ) , = \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ^ { n } \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ^ { n } \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ^ { n } \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ^ { - 1 } ( t - 1 ) \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ( t - 1 ) , \\mathrm { ~ \\ } _ { N } ( t - 1 ) , } \\\\ & { \\mathrm { \\ } _ { N _ { 4 } } ( t ) , \\equiv , \\ \\cdot \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } ( t - 1 ) . \\mathrm { ~ } N _ { 2 } ( t - 1 ) \\vee N _ { 3 } ( t - 1 ) . \\mathrm { ~ } _ { \\textnormal { \\tiny { F C } } } \\cdot N _ { 1 } ( t - 1 ) . \\mathrm { ~ } N _ { 3 } ( t - 1 ) . \\mathrm { ~ } N _ { 1 } ( t - 1 ) } \\end{array}$ $\\begin{array} { r l } { { \\bf \\Pi } } & { { } ^ { I \\hat { \\bf { v } } _ { 4 } \\hat { \\bf { v } } _ { 5 } \\hat { \\bf { \\Pi } } _ { 1 } - \\hat { \\bf { \\Pi } } _ { 3 } } \\quad \\quad \\quad \\quad \\quad \\quad \\quad \\quad \\quad \\quad } \\\\ { { \\bf \\Pi } } & { { } ^ { N _ { 4 } ( t ) _ { 5 } } \\equiv _ { 5 } \\quad \\sim N _ { 1 } ( t - 2 ) . N _ { 2 } ( t - 2 ) \\vee N _ { 3 } ( t - 2 ) . \\vee . N _ { 1 } ( t - 2 ) . N _ { 2 } ( t - 2 ) . N _ { 3 } ( t - 2 ) } \\end{array}$\n\ng. ${ \\cal N } _ { 3 } ( t ) . \\equiv . { \\cal N } _ { 2 } ( t - 2 ) . \\sim { \\cal N } _ { 1 } ( t - 3 )$\n\nh. ${ \\cal N } _ { 2 } ( t ) . \\equiv . { \\cal N } _ { 1 } ( t - 1 ) . { \\cal N } _ { 1 } ( t - 2 )$\n\ni. $\\begin{array} { l } { \\mathsf { \\Pi } _ { N _ { 3 } ( t ) _ { \\sharp } } ^ { \\circ } = : \\mathsf { N } _ { 2 } ( t - 1 ) . \\mathsf { V } . \\mathsf { \\dot { N } } _ { 1 } ( t - 1 ) . \\mathsf { V } . \\mathsf { N } _ { 1 } ( t - 1 ) . ( E x ) t - 1 . \\mathsf { N } _ { 1 } ( x ) . \\mathsf { N } _ { 2 } ( x ) } \\end{array}$\n\n人工智能哲学\n\n32","previous_page":31,"next_page":33}