{"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":38,"pdf_page":46,"physical_index":46,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"4e1dfb756e0723c6b51a0a3370be0f249487278c875df2415cbc0c02e51c55c3"},"chapter":"人工智能哲学","content":"人工智能哲学\n\n$$\n( z _ { 2 } ) z _ { 1 } . p _ { 1 } ( z _ { 2 } ) \\equiv p _ { 2 } ( z _ { 2 } ) .  . S _ { i } \\equiv S _ { i } \\{ \\begin{array} { c } { { p 1 } } \\\\ { { p 2 } } \\end{array} \\}\\tag{10}\n$$\n\n$$\n\\begin{array} { r l } & { P r _ { m i } = \\ b { \\mathscr { F } } [ ( z _ { 1 } ) ( z _ { 2 } ) z _ { 1 } ( z _ { 3 } ) z z _ { p } : .  f ( z _ { 1 } , \\ z _ { 2 } , \\ z _ { 3 } )   } \\\\ & { \\qquad \\equiv 0 . \\vee . f ( z _ { 1 } , \\ z _ { 2 } , \\ z _ { 3 } ) = 1 { : } f ( z _ { 1 } , \\ z _ { 2 } , \\ z _ { 3 } )  } \\\\ & { \\qquad = 1 . \\equiv . p _ { z 3 } ( z _ { 2 } ) { : }  { : } S _ { i } ] \\ , } \\end{array}\n$$\n\n任何满足这个要求的 $S _ { i }$ 都能用如下形式的等效S来替代：\n\n$$\n( E f ) ( z _ { 2 } ) z _ { 1 } ( z _ { 3 } ) z z _ { p } : f \\in P r _ { m i } : f ( z _ { 1 } , \\ z _ { 2 } , \\ z _ { 3 } ) { \\stackrel { } { = } } 1 . \\equiv . p _ { z 3 } ( z _ { 2 } )\\tag{11}\n$$\n\n式中 $z z _ { p }$ 代表P。现在考虑 $\\alpha _ { \\textit { i } }$ 类别的这些序列，对 $\\alpha _ { i }$ ，\n\n$$\n\\begin{array} { r l } & { N _ { i } ( t ) : \\equiv : ( E \\varPhi ) ( x ) t ( m ) q : \\varPhi \\varepsilon \\propto \\varepsilon _ { i } : N _ { m } ( x ) . } \\\\ & { \\qquad \\equiv . \\ \\varPhi ( t , x , m ) { = } 1 \\qquad [ i { = } q { + } 1 , \\cdots , M ] } \\end{array}\\tag{12}\n$$\n\n对某个网成立。这些将被称为可理解的类别。我们把一组k类别生成的布尔环定义为可通过重复应用逻辑运算由k的元形成的那些类别的集合；即\n\n$$\n\\begin{array} { r l } & { R ( { h } ) ^ { \\scriptscriptstyle [ 1 ] } = p \\mathrm {  \\Large ~ \\Psi ~ } ^ { * } \\hat { \\lambda } \\mathrm {  \\Large ~ [ ( \\alpha ~ , ~ \\beta ~ ) _ { \\pm } ~ \\alpha ~ \\varepsilon ~ } k  \\alpha \\mathrm {  \\Large ~ \\varepsilon ~ } \\lambda : \\alpha , \\mathrm {  \\Large ~ \\beta ~ } \\varepsilon \\lambda .  } \\\\ & { \\mathrm {  \\large ~   ~ \\alpha ~ , ~ \\alpha ~ \\alpha ~ \\cdot ~ \\beta ~ , ~ \\alpha ~ \\vee ~ \\beta ~ } \\varepsilon \\lambda \\mathrm {  \\large ~  \\rule { 0 ex } { 5 ex } ] ~ } . } \\end{array}\n$$\n\n同时我们定义\n\n$$\n\\begin{array} { c } { { { \\overline { { { R } } } } ( k ) . = . R ( k ) - \\mathrm { \\Lambda } _ { 1 } { \\mathrm { \\Lambda } } ^ { * } p { \\mathrm { \\Lambda } } ^ { * } - { \\mathrm { \\Lambda } } ^ { * } k , } } \\\\ { { { R } _ { e } ( k ) = p { \\mathrm { \\Lambda } } ^ { * } { \\hat { \\lambda } } [ { \\mathrm { ( } } \\alpha { \\mathrm { , } } \\beta { \\mathrm { ) } } { \\mathrm { : } } \\alpha \\ \\varepsilon \\ k \\to \\alpha \\ \\varepsilon \\ \\lambda \\ . } } \\\\ { { \\to . - \\ \\alpha \\ , \\ \\alpha \\ . \\ \\ \\mathrm { ~ } \\ \\mathrm { \\Lambda } \\ \\beta \\ , \\ \\alpha \\ \\vee \\ \\mathrm { \\Lambda } \\mathrm { \\Lambda } ^ { \\mathrm { \\Lambda } } { \\mathrm { , } } \\ { \\mathrm { \\Lambda } } ^ { * } \\ \\alpha \\ \\varepsilon \\ \\hat { \\lambda } } } \\\\ { { { \\overline { { { R } } } } _ { e } ( k ) = { R } _ { e } ( k ) - \\mathrm { \\Lambda } _ { 1 } { \\mathrm { \\Lambda } } ^ { * } p { \\mathrm { \\Lambda } } ^ { * } - { \\mathrm { \\Lambda } } ^ { * } k , } } \\end{array}\n$$\n\n$$\n\\sigma \\left( \\Psi , \\ t \\right) = \\Phi \\left[ \\left( m \\right) . \\hat { \\Phi } \\left( t + 1 , \\ t , \\ m \\right) = \\Psi \\left( m \\right) \\right] \\ \\mathrm { ~ } _ { \\circ }\n$$\n\nRe(k)类别是仿照R(k)由k形成的，但是不仅通过重复应用逻辑运算，而且也要重复应用由 $S ( P ) ~ \\varepsilon S ~ ^ { \\textbf { \\em a } } \\alpha$ 替代特性 $P \\varepsilon \\ \\alpha$ 类别的运算。于是我们得出引理：\n\n[1]此处和以下分别以“R”和“h”替代原文中书写体R和希腊文k的字型。—译者\n\n38","previous_page":37,"next_page":39}