{"id":7496,"date":"2017-09-13T14:23:55","date_gmt":"2017-09-13T05:23:55","guid":{"rendered":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/?p=7496"},"modified":"2018-12-11T15:08:21","modified_gmt":"2018-12-11T06:08:21","slug":"michael-weisberg-%e3%83%af%e3%82%a4%e3%82%b9%e3%83%90%e3%83%bc%e3%82%b0-2013-simulation-and-similarity-%e6%9d%be%e7%8e%8b-%e6%94%bf%e6%b5%a9-%e8%a8%b3-2017-%e7%a7%91%e5%ad%a6%e3%81%a8%e3%83%a2","status":"publish","type":"post","link":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/?p=7496","title":{"rendered":"Michael Weisberg [\u30ef\u30a4\u30b9\u30d0\u30fc\u30b0] (2013) Simulation and Similarity; (\u677e\u738b \u653f\u6d69 \u8a33 2017) \u79d1\u5b66\u3068\u30e2\u30c7\u30eb"},"content":{"rendered":"<ul>\n<li>Michael <strong>Weisberg<\/strong>, 2013 (paperback 2015): <em>Simulation and Similarity &#8212; Using Models to Understanding the World.<\/em> New York: Oxford University Press, 190 pp. ISBN 978-0-19-026512-0.<\/li>\n<li>\u30de\u30a4\u30b1\u30eb\u30fb<strong>\u30ef\u30a4\u30b9\u30d0\u30fc\u30b0<\/strong> \u8457, <strong>\u677e\u738b<\/strong> \u653f\u6d69 \u8a33 (2017): <em>\u79d1\u5b66\u3068\u30e2\u30c7\u30eb &#8212; \u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306e\u54f2\u5b66\u5165\u9580<\/em>\u3002\u540d\u53e4\u5c4b\u5927\u5b66\u51fa\u7248\u4f1a, 290+22 pp. ISBN 978-4-8158-0872-3.<\/li>\n<\/ul>\n<p>\u82f1\u8a9e\u7248\u306f2013\u5e74\u306b\u51fa\u305f\u672c\u3067\u3001\u308f\u305f\u3057\u306f2016\u5e74\u306b\u5e97\u982d\u3067\u30da\u30fc\u30d1\u30fc\u30d0\u30c3\u30af\u3092\u898b\u3064\u3051\u3066\u8cb7\u3063\u305f\u3002\u79d1\u5b66\u306e\u77e5\u8b58\u306e\u3046\u3061\u3067\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306b\u3088\u3063\u3066\u5f97\u3089\u308c\u305f\u77e5\u898b\u306f(\u7406\u8ad6\u3084\u5b9f\u9a13\u3068\u304f\u3089\u3079\u3066)\u3069\u306e\u3088\u3046\u306a\u4f4d\u7f6e\u306b\u3042\u308b\u304b\u3092\u8003\u3048\u305f\u304b\u3063\u305f\u306e\u3067\u3001\u53c2\u8003\u306b\u306a\u308b\u3068\u671f\u5f85\u3057\u305f\u306e\u3060\u3002\u8aad\u307f\u306f\u3058\u3081\u305f\u304c\u7b2c3\u7ae0\u306e\u521d\u3081\u306e\u3042\u305f\u308a\u3067\u6b62\u307e\u3063\u3066\u3044\u305f\u30022017\u5e744\u6708\u306b\u65e5\u672c\u8a9e\u7248\u304c\u51fa\u305f\u306e\u3067\u305d\u3061\u3089\u3092\u304a\u3082\u306b\u8aad\u3080\u3053\u3068\u306b\u3057\u305f\u3002\u3053\u306e\u672c\u306b\u3064\u3044\u3066\u306f\u8aad\u66f8\u4f1a\u306b\u53c2\u52a0\u3057\u3066\u3044\u308b\u306e\u3067\u305d\u3053\u3067\u308f\u304b\u3063\u305f\u3053\u3068\u3082\u3042\u308b\u304c\u3001\u3053\u306e\u8aad\u66f8\u30e1\u30e2\u306b\u306f\u304a\u3082\u306b\u8aad\u66f8\u4f1a\u306b\u53c2\u52a0\u3059\u308b\u524d\u304b\u3089\u308f\u305f\u3057\u304c\u6c17\u306b\u304b\u3051\u3066\u3044\u305f\u3053\u3068\u3092\u66f8\u304f(\u305d\u306e\u8868\u73fe\u306f\u8aad\u66f8\u4f1a\u304b\u3089\u306e\u5f71\u97ff\u3082\u53d7\u3051\u3066\u3044\u308b\u304c)\u3002<\/p>\n<p>\u4e3b\u984c\u3067\u3042\u308b\u306f\u305a\u306e\u300c\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u300d\u306b\u3064\u3044\u3066\u306f\u3042\u307e\u308a\u8a73\u3057\u304f\u8ad6\u3058\u3066\u304a\u3089\u305a\u3001\u305d\u308c\u306b\u4f7f\u3046\u300c\u30e2\u30c7\u30eb\u300d\u3092\u304a\u3082\u306b\u8ad6\u3058\u3066\u3044\u308b\u3002\u65e5\u672c\u8a9e\u7248\u306e\u984c\u540d\u3082\u305d\u308c\u3092\u53cd\u6620\u3057\u3066\u3044\u308b\u3002<\/p>\n<p>\u8457\u8005\u306f\u30e2\u30c7\u30eb\u3092\u3001\u7269\u4f53\u306b\u3088\u308b\u30e2\u30c7\u30eb(physical 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(\u65e5\u672c\u8a9e\u7248\u3067\u306f\u300c\u4eba\u7a2e\u5206\u96e2\u300d\u3068\u3057\u3066\u3044\u308b\u304c\u4eba\u7a2e\u306b\u9650\u308b\u3053\u3068\u306f\u306a\u3044)\u306e\u30e2\u30c7\u30eb\u3002\u5404\u4eba\u304c\u8fd1\u304f\u306b\u81ea\u5206\u3068\u540c\u3058\u5c5e\u6027\u306e\u4eba\u304c\u3044\u308b\u306e\u3092\u597d\u3080\u3068\u3057\u3001\u79fb\u52d5\u3067\u304d\u308b\u3068\u3057\u305f\u3068\u304d\u3001\u4eba\u306e\u5c5e\u6027\u306e\u7a7a\u9593\u5206\u5e03\u306f\u3069\u3046\u306a\u308b\u304b\u3002\u6642\u9593\u3092\u96e2\u6563\u3067\u6271\u3044\u3001\u6642\u9593\u30b9\u30c6\u30c3\u30d7\u3054\u3068\u306b\u3042\u3089\u304b\u3058\u3081\u4e0e\u3048\u3089\u308c\u305f\u78ba\u7387\u306b\u5f93\u3063\u3066\u30e9\u30f3\u30c0\u30e0\u306b\u79fb\u52d5\u304c\u8d77\u3053\u308b\u3088\u3046\u306a\u8868\u73fe\u306b\u3057\u305f\u3002<\/li>\n<\/ul>\n<p>\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306b\u4f7f\u308f\u308c\u308b\u30e2\u30c7\u30eb\u3092\u5e83\u304f\u5c55\u671b\u3059\u308b\u305f\u3081\u306b<em>\u4ee3\u8868\u7684\u306a\u985e\u578b<\/em>\u3068\u3057\u3066\u3053\u306e3\u3064\u3092\u3068\u308a\u3042\u3052\u308b\u306e\u306f\u3082\u3063\u3068\u3082\u3060\u3068\u601d\u3046\u3002\u3057\u304b\u3057\u8457\u8005\u306f\u3059\u3079\u3066\u306e\u30e2\u30c7\u30eb\u3092\u3053\u306e3\u3064\u306b<em>\u5206\u985e<\/em>\u3057\u3088\u3046\u3068\u3059\u308b\u304c\u3001\u305d\u308c\u306b\u306f\u7121\u7406\u304c\u3042\u308b\u3068\u308f\u305f\u3057\u306f\u601d\u3046\u3002\u6570\u7406\u30e2\u30c7\u30eb\u3068\u6570\u5024\u8a08\u7b97\u30e2\u30c7\u30eb\u306f\u9023\u7d9a\u3057\u305f\u6982\u5ff5\u3060\u3068\u601d\u3046 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model)\u3068\u304b\u300c\u56f3\u5f0f\u300d(schema)\u3068\u304b\u547c\u3076\u3088\u3046\u306a\u3082\u306e\u3001\u3042\u308b\u3044\u306f\u52d5\u304b\u306a\u3044\u304c\u5b9f\u7269\u306b\u4f3c\u305f\u6a21\u578b\u306a\u3069\u3082\u542b\u3081\u308b\u306e\u3060\u304c\u3001\u305d\u308c\u30923\u3064\u306e\u985e\u306e\u3069\u308c\u304b\u306b(\u308f\u305f\u3057\u304b\u3089\u898b\u308b\u3068\u3080\u308a\u3084\u308a)\u542b\u3081\u3088\u3046\u3068\u3059\u308b(\u7b2c2\u7ae0\u672b)\u3002\u308f\u305f\u3057\u306e\u8003\u3048\u3067\u306f\u3001\u307e\u305a\u300c\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u300d\u3092\u3001\u30e2\u30c7\u30eb\u306e\u4e16\u754c\u306e\u4e2d\u3067\u6642\u9593\u3068\u3068\u3082\u306b\u5909\u5316\u304c\u304a\u3053\u308b\u3001\u305d\u306e\u5909\u5316\u304c(\u306a\u3093\u3089\u304b\u306e\u610f\u5473\u3067)\u73fe\u5b9f\u306e\u4e16\u754c\u3067\u8d77\u3053\u308b\u5909\u5316\u3068\u4f3c\u3066\u3044\u308b\u3001\u305d\u3057\u3066\u3001\u30e2\u30c7\u30eb\u306e\u4e2d\u3067\u8d77\u3053\u308b\u5909\u5316\u306f\u3001\u3042\u3089\u304b\u3058\u3081\u5909\u5316\u306e\u898f\u5247\u3068\u6700\u521d\u306e\u6642\u70b9(\u300c\u521d\u671f\u300d)\u3067\u306e\u72b6\u614b\u3068\u3092\u4e0e\u3048\u308c\u3070\u3001\u9032\u884c\u4e2d\u306b\u306f\u4eba\u306e\u5224\u65ad\u304c\u4ecb\u5165\u3057\u306a\u3044\u3067\u9032\u3080(\u4eba\u304c\u4ecb\u5165\u3059\u308b\u3068\u3057\u3066\u3082\u30d7\u30ed\u30b0\u30e9\u30e0\u3069\u304a\u308a\u306e\u3082\u306e\u306b\u9650\u308b)\u3001\u3068\u3044\u3046\u7279\u5fb4\u3092\u3082\u3064\u3082\u306e\u306b\u9650\u5b9a\u3057\u305f\u3046\u3048\u3067\u3001\u8b70\u8ad6\u306e\u5bfe\u8c61\u3092\u300c\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306b\u4f7f\u308f\u308c\u308b\u30e2\u30c7\u30eb\u300d\u306b\u9650\u5b9a\u3059\u308b\u3001\u3068\u3057\u305f\u307b\u3046\u304c\u3001\u672c\u66f8\u306e\u8b70\u8ad6\u304c\u6709\u52b9\u306a\u7bc4\u56f2\u304c\u660e\u78ba\u306b\u306a\u308b\u3068\u601d\u3046\u3002(\u8457\u8005\u306f\u308f\u3056\u3068\u9650\u5b9a\u3057\u306a\u304b\u3063\u305f\u306e\u3060\u304c\u3001\u305d\u308c\u306f\u6210\u529f\u3057\u3066\u3044\u306a\u3044\u3068\u601d\u3046\u3002)<\/p>\n<p>(\u306a\u304a\u3001\u540c\u3058\u30e2\u30c7\u30eb\u3067\u521d\u671f\u72b6\u614b\u3060\u3051\u3092\u5909\u3048\u3066\u4f55\u5ea6\u3082\u6642\u9593\u5909\u5316\u3092\u9032\u884c\u3055\u305b\u305f\u3068\u304d\u3001\u8907\u6570\u306e\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u3057\u305f\u3068\u3044\u3046\u3079\u304d\u304b\u3001\u8907\u6570\u306erun\u3092\u542b\u3080\u3072\u3068\u3064\u306e\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u3057\u305f\u3068\u3044\u3046\u3079\u304d\u304b\u3001\u308f\u305f\u3057\u306f\u8868\u73fe\u306b\u306a\u3084\u3080\u3053\u3068\u304c\u3042\u308b\u306e\u3060\u304c\u3001\u3053\u306e\u70b9\u3082\u672c\u66f8\u3067\u306f\u3069\u3046\u3044\u3046\u614b\u5ea6\u3092\u3068\u3063\u3066\u3044\u308b\u306e\u304b\u3088\u304f\u308f\u304b\u3089\u306a\u304b\u3063\u305f\u3002)<\/p>\n<p>\u7b2c4\u7ae0\u306f\u3001\u54f2\u5b66\u306e\u5b58\u5728\u8ad6\u306e\u7acb\u5834\u304b\u3089\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3(\u3068\u3044\u3046\u8868\u73fe\u306f\u3057\u3066\u3044\u306a\u3044\u304c)\u306f\u30d5\u30a3\u30af\u30b7\u30e7\u30f3\u3068\u540c\u985e\u306a\u306e\u304b\u3001\u3068\u3044\u3046\u8b70\u8ad6\u3092\u3057\u3066\u3044\u308b\u3088\u3046\u3060\u304c\u3001\u308f\u305f\u3057\u306f\u307e\u3060\u3057\u3063\u304b\u308a\u8aad\u3093\u3067\u3044\u306a\u3044\u3002<\/p>\n<p>\u7b2c5\u7ae0\u304b\u3089\u7b2c7\u7ae0\u3067\u3001\u30e2\u30c7\u30eb\u3092\u3064\u304f\u308b\u6d3b\u52d5\u3092\u898b\u308b\u7acb\u5834\u304b\u3089\u3001\u30e2\u30c7\u30eb\u3068\u73fe\u5b9f\u4e16\u754c\u306e\u5bfe\u8c61\u3068\u306e\u95a2\u4fc2\u3092\u5206\u985e\u3057\u3066\u8ad6\u3058\u308b\u3002\u8868\u73fe\u3057\u305f\u3044\u5bfe\u8c61\u304c\u660e\u78ba\u306b\u3042\u308b\u5834\u5408\u3001\u5bfe\u8c61\u3092\u7406\u60f3\u5316(\u4e00\u822c\u5316\u3068\u3044\u3046\u3079\u304d\u304b\u3082\u3057\u308c\u306a\u3044)\u3057\u305f\u3082\u306e\u3092\u6271\u3046\u5834\u5408\u3001\u73fe\u5b9f\u4e16\u754c\u306b\u306f\u76f4\u63a5\u306e\u5bfe\u5fdc\u7269\u304c\u306a\u3044\u5834\u5408\u3001\u3068\u5206\u3051\u3066\u3001\u305d\u308c\u305e\u308c\u8ad6\u3058\u3066\u3044\u308b\u3002<\/p>\n<p>\u7b2c6\u7ae0\u306e\u300c\u7406\u60f3\u5316\u300d\u306e3\u985e\u578b\u306e\u3046\u3061\u3001\u300c\u30ac\u30ea\u30ec\u30a4\u578b\u300d\u3068\u300c\u30df\u30cb\u30de\u30ea\u30b9\u30c8\u300d\u306f\u3044\u305a\u308c\u3082\u3001\u73fe\u5b9f\u306b\u306f\u3042\u308b\u30d7\u30ed\u30bb\u30b9\u3067\u3042\u3063\u3066\u3082\u3001\u8ad6\u3058\u305f\u3044\u56e0\u679c\u30e1\u30ab\u30cb\u30ba\u30e0\u306b\u3068\u3063\u3066\u91cd\u8981\u3067\u306a\u3044\u3082\u306e\u306f\u7701\u7565\u3059\u308b\u3001\u3068\u3044\u3046\u614b\u5ea6\u3092\u793a\u3057\u3066\u3044\u308b\u3088\u3046\u3060\u3002\u3061\u304c\u3044\u306f\u3001\u300c\u30ac\u30ea\u30ec\u30a4\u578b\u300d\u306f\u7701\u7565\u3057\u305f\u3082\u306e\u3082\u5b66\u554f\u306e\u9032\u5c55\u306e\u306a\u304b\u3067\u306f\u542b\u3081\u3066\u3044\u304f\u3053\u3068\u3092\u6307\u5411\u3059\u308b\u304c\u300c\u30df\u30cb\u30de\u30ea\u30b9\u30c8\u300d\u306f\u305d\u3046\u3067\u306f\u306a\u3044\u3068\u3044\u3046\u3053\u3068\u3060\u308d\u3046\u304b? \u300c\u591a\u91cd\u30e2\u30c7\u30eb\u306b\u3088\u308b\u7406\u60f3\u5316\u300d\u3068\u547c\u3070\u308c\u3066\u3044\u308b\u3082\u306e\u306f\u3080\u3057\u308d\u7b2c9\u7ae0\u3067\u3044\u3046robustness\u3092\u78ba\u4fdd\u3059\u308b\u305f\u3081\u306e\u30e2\u30c7\u30ea\u30f3\u30b0\u7814\u7a76\u306e\u614b\u5ea6\u3060\u3068\u601d\u3046\u3002<\/p>\n<p>\u7b2c8\u7ae0\u3082\u30e2\u30c7\u30eb\u3068\u73fe\u5b9f\u4e16\u754c\u306e\u95a2\u4fc2\u3060\u304c\u3001\u3068\u304f\u306b\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306e\u7d50\u679c\u3068\u73fe\u5b9f\u4e16\u754c\u306e\u3082\u306e\u3054\u3068\u3068\u306e\u985e\u4f3c\u6027\u3092\u554f\u984c\u306b\u3059\u308b\u3002\u3053\u3053\u306b\u306f\u8a18\u53f7\u8ad6\u7406\u3068\u540c\u985e\u3068\u601d\u308f\u308c\u308b\u6570\u5f0f\u306e\u3088\u3046\u306a\u8868\u73fe\u304c\u305f\u3073\u305f\u3073\u51fa\u3066\u304f\u308b\u304c\u3001\u308f\u305f\u3057\u306f\u307e\u3060\u305d\u308c\u3092\u8ffd\u3044\u304b\u3051\u3066\u8aad\u3093\u3067\u3044\u306a\u3044\u3002<\/p>\n<p>\u7b2c9\u7ae0\u306f\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3067\u5f97\u3089\u308c\u305f\u77e5\u898b\u306e\u9811\u5065\u6027(robustness)\u3092\u554f\u984c\u306b\u3059\u308b\u3002\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3067\u306f(\u305f\u3044\u3066\u3044)\u73fe\u5b9f\u4e16\u754c\u306b\u3064\u3044\u3066\u306e\u77e5\u898b\u3092\u8a3c\u660e\u3059\u308b\u3053\u3068\u306f\u3067\u304d\u306a\u3044\u3002\u3057\u304b\u3057\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u306b\u3088\u3063\u3066\u73fe\u5b9f\u4e16\u754c\u306b\u3064\u3044\u3066(\u76f8\u5bfe\u7684\u306b)\u9811\u5065\u306a\u77e5\u898b\u3092\u5f97\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/p>\n<p>\u65e5\u672c\u8a9e\u7248\u306e\u300c\u30ed\u30d0\u30b9\u30c8\u6761\u4ef6\u300d\u3068\u300c\u30ed\u30d0\u30b9\u30c8\u5206\u6790\u300d\u3068\u3044\u3046\u7528\u8a9e\u306f\u308f\u304b\u308a\u306b\u304f\u3044\u3002\u300c\u30ed\u30d0\u30b9\u30c8\u6761\u4ef6\u300d\u3068\u306a\u3063\u3066\u3044\u308b\u306e\u306f <em>robust theorem<\/em>\u3060\u3002Theorem\u306f\u3001\u300c\u5b9a\u7406\u300d\u3068\u76f4\u8a33\u3057\u3066\u3082\u308f\u304b\u308a\u306b\u304f\u3044\u304c\u3001\u77e5\u898b(\u77e5\u8b58\u306e\u65ad\u7247)\u306e\u3046\u3061\u3067\u3082\u6c4e\u7528\u6027\u306e\u3042\u308b\u5f62\u3067\u5b9a\u5f0f\u5316\u3055\u308c\u3066\u3044\u308b\u3082\u306e\u3092\u3055\u3059\u306e\u3060\u3068\u601d\u3046\u3002\u305d\u308c\u304crobust\u3060\u3068\u3044\u3046\u306e\u306f\u3001Wimsatt\u306e\u8b70\u8ad6\u306b\u5f93\u3063\u3066\u3001\u591a\u6570\u306e\u601d\u8003\u7d4c\u8def\u306b\u3088\u3063\u3066\u3055\u3055\u3048\u3089\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u3055\u3059\u306e\u3060\u3068\u601d\u3046\u3002\u300c\u30ed\u30d0\u30b9\u30c8\u5206\u6790\u300d\u3068\u306a\u3063\u3066\u3044\u308b\u306e\u306f<em>robustness analysis<\/em>\u3067\u3001\u3042\u308b\u77e5\u898b\u304crobust\u3067\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u8a55\u4fa1\u3059\u308b\u3053\u3068(\u305d\u306e\u624b\u7d9a\u304d\u3084\u8a55\u4fa1\u57fa\u6e96\u3092\u542b\u3080)\u3092\u3055\u3057\u3066\u3044\u308b\u3068\u601d\u3046\u3002\u3010[2018-12-11\u88dc\u8db3] \u308f\u305f\u3057\u306e\u7528\u8a9e\u3068\u3057\u3066\u306f\u300c\u9811\u5065\u306a\u77e5\u898b\u300d\u3068\u300c\u9811\u5065\u6027\u5206\u6790\u300d\u3068\u3057\u3066\u304a\u304d\u305f\u3044\u3002\u3011<\/p>\n<p>Robustness analysis\u306e\u3046\u3061\u3001\u3057\u304b\u3051\u304c\u5c0f\u3055\u3044\u3082\u306e(\u5f97\u3089\u308c\u308brobustness\u3082\u5c0f\u3055\u3044\u3060\u308d\u3046)\u306f\u3001\u30e2\u30c7\u30eb\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u5024\u3092\u5909\u3048\u3066\u307f\u308b\u3082\u306e\u3060\u3002\u305d\u306e\u6b21\u304c\u3001\u30e2\u30c7\u30eb\u306e\u69cb\u9020\u3092\u3044\u304f\u3089\u304b\u5909\u5316\u3055\u305b\u308b(\u305f\u3068\u3048\u3070\u30d7\u30ed\u30bb\u30b9\u3092\u8ffd\u52a0\u3057\u305f\u308a\u53d6\u308a\u9664\u3044\u305f\u308a\u3057\u3066\u307f\u308b)\u3082\u306e\u3060\u3002\u3055\u3089\u306b\u5927\u304d\u3044\u306e\u304c\u3001\u307e\u3063\u305f\u304f\u3061\u304c\u3046\u7d44\u307f\u7acb\u3066\u306e\u30e2\u30c7\u30eb\u3067\u540c\u3058\u56e0\u679c\u30e1\u30ab\u30cb\u30ba\u30e0\u306e\u8868\u73fe\u3092\u8a66\u307f\u308b\u3053\u3068\u3060\u3002(Lotka-Volterra\u30e2\u30c7\u30eb\u3067\u8d77\u3053\u308b\u3053\u3068\u3092Schelling\u30e2\u30c7\u30eb\u3068\u4f3c\u305f\u3057\u304b\u3051\u3067\u30b7\u30df\u30e5\u30ec\u30fc\u30c8\u3057\u305f\u4f8b\u304c\u7d39\u4ecb\u3055\u308c\u3066\u3044\u308b\u3002) \u3053\u306e\u8b70\u8ad6\u306f\u3001\u6c17\u5019\u30e2\u30c7\u30eb\u95a2\u4fc2\u8005\u304c\u5b9f\u969b\u306b\u3084\u3063\u3066\u3044\u308b\u3053\u3068\u3068\u540c\u3058\u3060\u3068\u601d\u3046\u3002\u5225\u306e\u5c02\u9580\u306e\u7528\u8a9e\u3067\u8868\u73fe\u3057\u3066\u304f\u308c\u305f\u306e\u306f\u53c2\u8003\u306b\u306a\u308b\u3068\u601d\u3063\u305f\u304c\u3001\u308f\u305f\u3057\u306b\u3068\u3063\u3066\u3068\u304f\u306b\u65b0\u3057\u3044\u77e5\u8b58\u304c\u5f97\u3089\u308c\u305f\u308f\u3051\u3067\u3082\u306a\u3044\u3068\u601d\u3063\u305f\u3002<\/p>\n<p>\u6298\u308a\u8fd4\u3057\u306e\u3042\u3068\u306b\u76ee\u6b21\u3092\u3064\u3051\u308b\u3002\u7ae0\u30fb\u7bc0\u30fb\u5c0f\u7bc0\u305d\u308c\u305e\u308c\u306b\u3064\u3044\u3066\u3001\u307e\u305a\u65e5\u672c\u8a9e\u7248\u306e\u984c\u76ee\u3001\u305d\u306e\u3042\u3068\u306b\u82f1\u8a9e\u7248\u306e\u984c\u76ee\u3092\u3042\u3052\u305f\u3002\u305f\u3060\u3057\u7bc0\u30fb\u5c0f\u7bc0\u306e\u756a\u53f7\u306e\u793a\u3057\u304b\u305f\u306f\u3001\u82f1\u8a9e\u7248\u306b\u306a\u3089\u3063\u3066\u5c0f\u6570\u70b9\u306e\u3088\u3046\u306b\u30d4\u30ea\u30aa\u30c9\u3092\u4f7f\u3063\u3066\u793a\u3059\u65b9\u5f0f\u3092\u3068\u3063\u305f (\u65e5\u672c\u8a9e\u7248\u306f\u7bc0\u30fb\u5c0f\u7bc0\u756a\u53f7\u3060\u3051\u3067\u3001\u5c0f\u7bc0\u756a\u53f7\u306f\u30ab\u30c3\u30b3\u3064\u304d\u3067\u793a\u3059\u5f62\u306b\u306a\u3063\u3066\u3044\u308b\u3002)<br \/>\n<!--more--><br \/>\n== \u76ee\u6b21 ==<br \/>\n\u76ee\u6b21 Contents<br \/>\n#List of Figures<br \/>\n#List of Tables<br \/>\n\u51e1\u4f8b<br \/>\n\u5e8f\u6587 Preface<br \/>\n1. \u306f\u3058\u3081\u306b Introduction<br \/>\n &#8211; 1.1 \u6c34\u3092\u3081\u3050\u308b\u4e8c\u3064\u306e\u96e3\u554f Two Aquatic Puzzles<br \/>\n &#8211; 1.2 \u30e2\u30c7\u30ea\u30f3\u30b0\u306e\u30e2\u30c7\u30eb Models of Modeling<br \/>\n2. \u4e09\u3064\u306e\u7a2e\u985e\u306e\u30e2\u30c7\u30eb Three Kinds of Models<br \/>\n &#8211; 2.1 \u5177\u8c61\u30e2\u30c7\u30eb &#8212; \u30b5\u30f3\u30d5\u30e9\u30f3\u30b7\u30b9\u30b3\u6e7e-\u30c7\u30eb\u30bf\u5730\u5e2f\u30e2\u30c7\u30eb Concrete Model: The San Francisco Bay-Delta Model<br \/>\n &#8211; 2.2 \u6570\u7406\u30e2\u30c7\u30eb &#8212; \u30ed\u30c8\u30ab-\u30f4\u30a9\u30eb\u30c6\u30e9\u30e2\u30c7\u30eb Mathematical Model: Lotka-Volterra Model<br \/>\n &#8211; 2.3 \u6570\u5024\u8a08\u7b97\u30e2\u30c7\u30eb &#8212; \u30b7\u30a7\u30ea\u30f3\u30b0\u306e\u4eba\u7a2e\u5206\u96e2\u30e2\u30c7\u30eb Computational Model: Schelling&#8217;s Segregation Model<br \/>\n &#8211; 2.4 \u3053\u308c\u3089\u306e\u30e2\u30c7\u30eb\u306b\u5171\u901a\u3059\u308b\u7279\u5fb4 Common Features of these Models<br \/>\n &#8211; 2.5 \u30e2\u30c7\u30eb\u306f\u4e09\u7a2e\u985e\u3060\u3051\u304b? Only Three Types of Models?<br \/>\n &#8211; 2.6 \u30e2\u30c7\u30eb\u306f\u4e09\u7a2e\u985e\u3088\u308a\u3082\u5c11\u306a\u3044\u304b? Fewer than Three Types of Model?<br \/>\n3. \u30e2\u30c7\u30eb\u306e\u69cb\u6210 The Anatomy of Models<br \/>\n &#8211; 3.1 \u69cb\u9020 Structure<br \/>\n &#8211; &#8211; 3.1.1 \u5177\u8c61\u7684\u306a\u69cb\u9020 Concrete Structures<br \/>\n &#8211; &#8211; 3.1.2 \u6570\u5b66\u7684\u69cb\u9020 Mathematical Structures<br \/>\n &#8211; &#8211; 3.1.3 \u6570\u5024\u8a08\u7b97\u306e\u69cb\u9020 Computational Structures<br \/>\n &#8211; 3.2 \u30e2\u30c7\u30eb\u8a18\u8ff0 Model Descriptions<br \/>\n &#8211; 3.3 \u89e3\u91c8 Construal<br \/>\n &#8211; 3.4 \u69cb\u9020\u306e\u8868\u73fe\u80fd\u529b Reprentational Capacity of Structures<br \/>\n4. \u30d5\u30a3\u30af\u30b7\u30e7\u30f3\u3068\u6163\u7fd2\u7684\u5b58\u5728\u8ad6 Fictions and Folk Ontology<br \/>\n &#8211; 4.1 \u6570\u7406\u69cb\u9020\u4e2d\u5fc3\u8aac\u306b\u53cd\u5bfe\u3057\u3066 &#8212; \u500b\u5225\u5316\u3001\u56e0\u679c\u3001\u984d\u9762\u901a\u308a\u306e\u5b9f\u8df5\u3001\u3068\u3044\u3046\u554f\u984c Aganist Maths: Indibuation, Causes, and Face-Value Practice<br \/>\n &#8211; 4.2 \u30b7\u30f3\u30d7\u30eb\u306a\u30d5\u30a3\u30af\u30b7\u30e7\u30f3\u7684\u8aac\u660e A Simple Fictions Account<br \/>\n &#8211; 4.3 \u30b7\u30f3\u30d7\u30eb\u306a\u8aac\u3092\u5f37\u5316\u3059\u308b Enriching the Simple Account<br \/>\n &#8211; &#8211; 4.3.1 \u30a6\u30a9\u30eb\u30c8\u30f3\u7684\u306a\u30d5\u30a3\u30af\u30b7\u30e7\u30f3\u4e3b\u7fa9 Waltonian Fictionalism<br \/>\n &#8211; &#8211; 4.3.2 \u30e2\u30c7\u30eb\u306a\u3057\u306e\u30d5\u30a3\u30af\u30b7\u30e7\u30f3 Fictions Without Models<br \/>\n &#8211; 4.4 \u306a\u305c\u79c1\u306f\u30d5\u30a3\u30af\u30b7\u30e7\u30f3\u4e3b\u7fa9\u8005\u3067\u306f\u306a\u3044\u306e\u304b Why I Am Not a Fictionalist<br \/>\n &#8211; &#8211; 4.4.1 \u5dee\u7570 Variation<br \/>\n &#8211; &#8211; 4.4.2 \u7570\u306a\u308b\u30e2\u30c7\u30eb\u3092\u8868\u73fe\u3059\u308b\u80fd\u529b Representational Capacity of Different Models<br \/>\n &#8211; &#8211; 4.4.3 \u30e2\u30c7\u30ea\u30f3\u30b0\u3092\u7406\u89e3\u3059\u308b\u3053\u3068 Making Sense of Modeling<br \/>\n &#8211; &#8211; 4.4.4 \u5b9f\u8df5\u884c\u70ba\u306b\u304a\u3051\u308b\u5dee\u7570 Variation in Practice<br \/>\n &#8211; 4.5 \u6163\u7fd2\u7684\u5b58\u5728\u8ad6 Folk Ontology<br \/>\n &#8211; 4.6 \u6570\u5b66\u3001\u89e3\u91c8\u3001\u304a\u3088\u3073\u6163\u7fd2\u7684\u5b58\u5728\u8ad6 Maths, Interpretation, and Folk Ontology<br \/>\n5. \u5bfe\u8c61\u6307\u5411\u578b\u30e2\u30c7\u30ea\u30f3\u30b0 Target-Directed Modeling<br \/>\n &#8211; 5.1 \u30e2\u30c7\u30eb\u306e\u4f5c\u308a\u4e0a\u3052 Model Development<br \/>\n &#8211; 5.2 \u30e2\u30c7\u30eb\u306e\u5206\u6790 Analysis of the Model<br \/>\n &#8211; &#8211; 5.2.1 \u5341\u5168\u5206\u6790 Complete Analysis<br \/>\n &#8211; &#8211; 5.2.2 \u76ee\u7684\u5fd7\u5411\u578b\u306e\u5206\u6790 Goal-Directed Analysis<br \/>\n &#8211; 5.3 \u30e2\u30c7\u30eb\u3068\u5bfe\u8c61\u306e\u6bd4\u8f03 Model-Target Comparison<br \/>\n &#8211; &#8211; 5.3.1 \u73fe\u8c61\u3068\u5bfe\u8c61\u30b7\u30b9\u30c6\u30e0 Phenomena and Target Systems<br \/>\n &#8211; &#8211; 5.3.2 \u30e2\u30c7\u30eb\u3068\u5bfe\u8c61\u306e\u9069\u5408\u6027\u3092\u78ba\u304b\u3081\u308b Establishing the Fit between Model and Target<br \/>\n &#8211; &#8211; 5.3.3 \u5bfe\u8c61\u306e\u8868\u73fe Representations of Targets<br \/>\n6. \u7406\u60f3\u5316 Idealization<br \/>\n &#8211; 6.1 \u4e09\u3064\u306e\u7a2e\u985e\u306e\u7406\u60f3\u5316 Three Kinds of Idealization<br \/>\n &#8211; &#8211; 6.1.1 \u30ac\u30ea\u30ec\u30a4\u7684\u7406\u60f3\u5316 Galilean Idealization<br \/>\n &#8211; &#8211; 6.1.2 \u30df\u30cb\u30de\u30ea\u30b9\u30c8\u306e\u7406\u60f3\u5316 Minimalist Idealization<br \/>\n &#8211; &#8211; 6.1.3 \u591a\u91cd\u30e2\u30c7\u30eb\u306b\u3088\u308b\u7406\u60f3\u5316 Multiple-Models Idealization<br \/>\n &#8211; 6.2 \u8868\u73fe\u7684\u7406\u60f3\u3068\u5fe0\u5b9f\u5ea6\u57fa\u6e96 Representational Ideals and Fidelity Criteria<br \/>\n &#8211; &#8211; 6.2.1 \u5b8c\u5168\u6027 Completeness<br \/>\n &#8211; &#8211; 6.2.2 \u5358\u7d14\u6027 Simplicity<br \/>\n &#8211; &#8211; 6.2.3 \u4e00\u610f\u56e0\u679c\u6027 1-Causal<br \/>\n &#8211; &#8211; 6.2.4 \u51fa\u529b\u6700\u5927\u6027 Maxout<br \/>\n &#8211; &#8211; 6.2.5 P-\u4e00\u822c\u6027 P-General<br \/>\n &#8211; 6.3 \u7406\u60f3\u5316\u3068\u8868\u73fe\u7684\u7406\u60f3 Idealizatoin and Representaitonal Ideals<br \/>\n &#8211; 6.4 \u7406\u60f3\u5316\u3068\u5bfe\u8c61\u6307\u5411\u578b\u30e2\u30c7\u30ea\u30f3\u30b0 Idealization and Target-Directed Modeling<br \/>\n7. \u7279\u5b9a\u306e\u5bfe\u8c61\u306a\u3057\u306e\u30e2\u30c7\u30ea\u30f3\u30b0 Modeling Without a Specific Target<br \/>\n &#8211; 7.1 \u6c4e\u5316\u30e2\u30c7\u30ea\u30f3\u30b0 Generalized Modeling<br \/>\n &#8211; &#8211; 7.1.1 \u4e00\u4f53\u3069\u3046\u3057\u3066\u3001\u3068\u3044\u3046\u554f\u3044\u3078\u306e\u8aac\u660e How-Possibly Explanations<br \/>\n &#8211; &#8211; 7.1.2 \u6700\u5c0f\u30e2\u30c7\u30eb\u3068\u7b2c\u4e00\u6b21\u306e\u56e0\u679c\u7684\u69cb\u9020 Minimal Models and First-Order Causal Structures<br \/>\n &#8211; 7.2 \u4eee\u8aac\u7684\u30e2\u30c7\u30ea\u30f3\u30b0 Hypothetical Modeling<br \/>\n &#8211; &#8211; 7.2.1 \u5076\u7136\u7684\u306a\u975e\u5b58\u5728 &#8212; xDNA Contigent Nonexixtence: xDNA<br \/>\n &#8211; &#8211; 7.2.2 \u4e0d\u53ef\u80fd\u306a\u5bfe\u8c61 &#8212; \u7121\u9650\u306e\u500b\u4f53\u7fa4\u751f\u9577\u3068\u6c38\u4e45\u904b\u52d5 Impossible Targets: Infinite Population Growth and Perpetual Motion<br \/>\n &#8211; 7.3 \u5bfe\u8c61\u306a\u3057\u30e2\u30c7\u30ea\u30f3\u30b0 Targetless Modeling<br \/>\n &#8211; 7.4 \u63fa\u308c\u52d5\u304f\u5bfe\u8c61 &#8212; \u4e09\u3064\u306e\u6027\u306e\u751f\u7269\u5b66 A Moving Target: The Case of Three-sex Biology<br \/>\n8. \u985e\u4f3c\u6027\u306e\u8aac\u660e An Account of Similarity<br \/>\n &#8211; 8.1 \u30e2\u30c7\u30eb-\u4e16\u754c\u9593\u95a2\u4fc2\u306b\u5fc5\u8981\u306a\u3053\u3068 Desiderata for Model-World Relations<br \/>\n &#8211; 8.2 \u30e2\u30c7\u30eb\u7406\u8ad6\u7684\u8aac\u660e Model-Theoretic Accounts<br \/>\n &#8211; 8.3 \u985e\u4f3c\u6027 Similarity<br \/>\n &#8211; 8.4 \u30c8\u30f4\u30a7\u30eb\u30b9\u30ad\u30fc\u306e\u5bfe\u7167\u7684\u8aac\u660e Tversky&#8217;s Contrast Account<br \/>\n &#8211; 8.5 \u5c5e\u6027\u3068\u30e1\u30ab\u30cb\u30ba\u30e0 Attributes and Mechanisms<br \/>\n &#8211; 8.6 \u7279\u5fb4\u96c6\u5408\u3001\u89e3\u91c8\u3001\u5bfe\u8c61\u30b7\u30b9\u30c6\u30e0 Feature Sets, Construals, and Target Systems<br \/>\n &#8211; 8.7 \u30e2\u30c7\u30ea\u30f3\u30b0\u306e\u76ee\u7684\u3068\u91cd\u307f\u3065\u3051\u306e\u30d1\u30e9\u30e1\u30fc\u30bf Modeling Goals and Weighing Parameters<br \/>\n &#8211; 8.8 \u91cd\u307f\u3065\u3051\u95a2\u6570\u3068\u80cc\u666f\u7406\u8ad6 Weighting Function and Background Theory<br \/>\n &#8211; 8.9 \u5fc5\u8981\u4e8b\u9805\u3092\u6e80\u305f\u3059 Satisfying the Desiderata<br \/>\n9. \u30ed\u30d0\u30b9\u30c8\u5206\u6790\u3068\u7406\u60f3\u5316 Robustness Analysis and Idealization<br \/>\n &#8211; 9.1 \u30ed\u30d0\u30b9\u30c8\u30cd\u30b9\u306b\u95a2\u3059\u308b\u8b70\u8ad6 &#8211; \u30ec\u30f4\u30a3\u30f3\u30ba\u3068\u30a6\u30a3\u30e0\u30b5\u30c3\u30c8 Levins and Wimsatt on Robustness<br \/>\n &#8211; 9.2 \u30ed\u30d0\u30b9\u30c8\u6761\u4ef6\u3092\u898b\u3064\u3051\u308b Finding Robust Theorems<br \/>\n &#8211; 9.3 \u4e09\u7a2e\u985e\u306e\u30ed\u30d0\u30b9\u30c8\u30cd\u30b9 Three Kinds of Robustness<br \/>\n &#8211; &#8211; 9.3.1 \u30d1\u30e9\u30e1\u30fc\u30bf\u30fb\u30ed\u30d0\u30b9\u30c8\u30cd\u30b9 Parameter Robustness<br \/>\n &#8211; &#8211; 9.3.2 \u69cb\u9020\u30ed\u30d0\u30b9\u30c8\u30cd\u30b9 Structural Robustness<br \/>\n &#8211; &#8211; 9.3.3 \u8868\u73fe\u30ed\u30d0\u30b9\u30c8\u30cd\u30b9 Representational Robustness<br \/>\n &#8211; 9.4 \u30ed\u30d0\u30b9\u30c8\u30cd\u30b9\u3068\u78ba\u8a3c Robustness and Confirmation<br \/>\n10. \u304a\u308f\u308a\u306b &#8212; \u30e2\u30c7\u30ea\u30f3\u30b0\u3068\u3044\u3046\u884c\u70ba Conclusion: The Practice of Modeling<br \/>\n\u8a33\u8005\u89e3\u8aac<br \/>\n &#8211; \u672c\u66f8\u306e\u7279\u5fb4<br \/>\n &#8211; &#8211; (1) \u5e83\u7bc4\u306a\u79d1\u5b66\u306e\u30e2\u30c7\u30eb\u3001\u30e2\u30c7\u30ea\u30f3\u30b0\u304c\u30ab\u30d0\u30fc\u3055\u308c\u3066\u3044\u308b\u3053\u3068<br \/>\n &#8211; &#8211; (2) \u4e3b\u8981\u306a\u54f2\u5b66\u7684\u8b70\u8ad6\u3068\u306e\u95a2\u4fc2\u304c\u660e\u78ba\u306b\u8ff0\u3079\u3089\u308c\u3066\u3044\u308b\u3053\u3068<br \/>\n &#8211; \u5f93\u6765\u7684\u306a\u8b70\u8ad6\u3068\u306e\u30ae\u30e3\u30c3\u30d7<br \/>\n &#8211; &#8211; (1) \u6570\u7406\u30e2\u30c7\u30eb\u306e\u4f4d\u7f6e\u3065\u3051<br \/>\n &#8211; &#8211; (2) \u8b70\u8ad6\u306e\u898f\u7bc4\u7684\u5c04\u7a0b<br \/>\n &#8211; \u304a\u308f\u308a\u306b<br \/>\n\u53c2\u8003\u6587\u732e References<br \/>\n\u6ce8<br \/>\n\u7d22\u5f15 Index<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Michael Weisberg, 2013 (paperback 2015): Simulation and Similarity &#8212; Using Models to Understanding the W [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-7496","post","type-post","status-publish","format-standard","hentry","category-dokusyo-memo-"],"_links":{"self":[{"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/posts\/7496","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7496"}],"version-history":[{"count":12,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/posts\/7496\/revisions"}],"predecessor-version":[{"id":8345,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=\/wp\/v2\/posts\/7496\/revisions\/8345"}],"wp:attachment":[{"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7496"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7496"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/macroscope.world.coocan.jp\/yukukawa\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7496"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}