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than martingales used in traditional probability theory. Schnorr showed how the existence of a selective betting strategy implied the existence of a selection rule for a biased sub-sequence. If one only requires a recursive martingale to succeed on a sequence instead of constructively succeed on a
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The sub-sequence selection criterion imposed by von Mises is important, because although 0101010101... is not biased, by selecting the odd positions, we get 000000... which is not random. Von Mises never totally formalized his definition of a proper selection rule for sub-sequences, but in 1940
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avoids a definition of a random sequence. Traditional probability theory does not state if a specific sequence is random, but generally proceeds to discuss the properties of random variables and stochastic sequences assuming some definition of randomness. The
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independently proposed a more permissive selection rule. In their view Church's recursive function definition was too restrictive in that it read the elements in order. Instead they proposed a rule based on a partially computable process which having read
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approach. This approach started with the work of Richard von Mises and Alonzo Church. In the 1960s Per Martin-Löf noticed that the sets coding such frequency-based stochastic properties are a special kind of
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stated in 1951: "A random sequence is a vague notion... in which each term is unpredictable to the uninitiated and whose digits pass a certain number of tests traditional with statisticians".
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During the 20th century various technical approaches to defining random sequences were developed and now three distinct paradigms can be identified. In the mid 1960s,
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Laurant Bienvenu "Kolmogorov Loveland Stochasticity" in STACS 2007: 24th Annual Symposium on Theoretical Aspects of Computer Science by Wolfgang Thomas
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i.e. the frequency of zeros goes to 1/2 and every sub-sequence we can select from it by a "proper" method of selection is also not biased.
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elements of the sequence, decides if it wants to select another element which has not been read yet. This definition is often called
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who showed that there is a Kolmogorov–Loveland stochastic sequence which does not conform to the general notion of randomness.
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sets, and that a more general and smooth definition can be obtained by considering all effectively measure zero sets.
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in Automata, languages and programming: 29th international colloquium, ICALP 2002, by Peter Widmayer et al.
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which having read the first N elements of the sequence decides if it wants to select element number 
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In most cases, theorems relating the three paradigms (often equivalence) have been proven.
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introduced a new notion which is now generally considered the most satisfactory notion of
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approach. This paradigm was championed by A. N. Kolmogorov along with contributions from
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in Mathematical foundations of computer science 2004: by Jiří Fiala, Václav Koubek 2004
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showed that recursive randomness concept is different from Schnorr's randomness concept.
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Schnorr, C. P. (1971). "A unified approach to the definition of a random sequence".
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was one of the first mathematicians to formally address randomness in 1909. In 1919
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by Vladimir Andreevich UspenskiÄ­, AlekseÄ­, LĘąvovich Semenov 1993 Springer
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Three basic paradigms for dealing with random sequences have now emerged:
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Wang, Yongge (1999). "A separation of two randomness concepts".
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Les probabilites denombrables et leurs applications arithmetique
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considered the statement "let us consider a random sequence" an
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Three approaches to the quantitative definition of information
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An introduction to Kolmogorov complexity and its applications
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A new interpretation of von Mises' concept of random sequence
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sequence, then one gets the concept of recursive randomness.
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and many statistical discussions begin with the words "let
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Yongge Wang: Randomness and Complexity. PhD Thesis, 1996.
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by Ming Li, P. M. B. Vitányi 1997 0387948686 pages 149–151
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on frequency stability. Why humans can't "guess" randomly
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Problems of Information and Transmission, 1(1):1–7, 1965.
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and uses a slightly different definition of constructive
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rather than random sequence. Using the concept of the
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This paradigm is due to 97:impossibility of a gambling system 14: 687: 625: 608:Kolmogorov Loveland Stochasticity 317:The American Mathematical Monthly 153:Kolmogorov–Loveland stochasticity 656:Randomness tests by Terry Ritter 319:, Vol. 109, 2002, pp. 46–63 75: 600: 563: 551: 516: 495: 450:10.1090/S0002-9904-1940-07154-X 572:Information Processing Letters 483: 470: 457: 421: 404: 391: 371: 351: 330: 1: 594:10.1016/S0020-0190(98)00202-6 304: 189:frequency / measure-theoretic 87:gave the first definition of 338:Mathematics and common sense 207:complexity / compressibility 101:frequency stability property 58:Axiomatic probability theory 7: 638:Encyclopedia of Mathematics 525:Mathematical Systems Theory 272: 225:) normalized by the length 10: 692: 313:What Is a Random Sequence? 294:Seven states of randomness 340:by Philip J. Davis 2006 323: 176:universal Turing machine 289:Random number generator 125:Mises–Church randomness 676:Statistical randomness 299:Statistical randomness 168:algorithmic randomness 89:algorithmic randomness 437:Bull. Amer. Math. Soc 284:History of randomness 223:Kolmogorov complexity 172:Kolmogorov complexity 671:Sequences and series 360:by JĂłzsef Beck 2009 121:Church Turing Thesis 221:as the entropy (or 537:10.1007/bf01694181 463:A. N. Kolmogorov, 310:Sergio B. Volchan 113:recursive function 111:defined it as any 22:probability theory 633:"Random sequence" 606:Wolfgang Merkle, 131:Modern approaches 85:Richard von Mises 70:abuse of language 16:The concept of a 683: 646: 619: 604: 598: 597: 587: 567: 561: 555: 549: 548: 520: 514: 499: 493: 487: 481: 474: 468: 461: 455: 454: 452: 425: 419: 408: 402: 395: 389: 375: 369: 355: 349: 334: 252:Claus P. Schnorr 137:A. N. Kolmogorov 34:random variables 20:is essential in 691: 690: 686: 685: 684: 682: 681: 680: 661: 660: 631: 628: 623: 622: 605: 601: 568: 564: 556: 552: 521: 517: 500: 496: 488: 484: 476:D.W. Loveland, 475: 471: 462: 458: 426: 422: 409: 405: 396: 392: 376: 372: 356: 352: 335: 331: 326: 307: 275: 215:Gregory Chaitin 133: 78: 66:Bourbaki school 48: 42: 18:random sequence 12: 11: 5: 689: 679: 678: 673: 659: 658: 653: 647: 627: 626:External links 624: 621: 620: 599: 578:(3): 115–118. 562: 550: 531:(3): 246–258. 515: 494: 482: 469: 456: 443:(2): 130–136. 429:Church, Alonzo 420: 403: 390: 370: 350: 328: 327: 325: 322: 321: 320: 306: 303: 302: 301: 296: 291: 286: 281: 274: 271: 267: 266: 265: 264: 248:predictability 241: 240: 239: 238: 200: 199: 198: 197: 164:Per Martin-Löf 157:Alexander Shen 141:D. W. Loveland 132: 129: 77: 74: 46: 40: 9: 6: 4: 3: 2: 688: 677: 674: 672: 669: 668: 666: 657: 654: 651: 648: 644: 640: 639: 634: 630: 629: 617: 616:3-540-43864-5 613: 609: 603: 595: 591: 586: 585:10.1.1.46.199 581: 577: 573: 566: 560: 554: 546: 542: 538: 534: 530: 526: 519: 512: 511:3-540-22823-3 508: 504: 498: 491: 486: 479: 473: 466: 460: 451: 446: 442: 438: 434: 430: 424: 417: 416:3-540-70917-7 413: 407: 400: 394: 387: 386:0-7923-2210-X 383: 379: 374: 367: 366:0-8218-4756-2 363: 359: 354: 348:pages 180-182 347: 346:1-56881-270-1 343: 339: 333: 329: 318: 315: 314: 309: 308: 300: 297: 295: 292: 290: 287: 285: 282: 280: 277: 276: 270: 262: 257: 253: 249: 245: 244: 243: 242: 236: 232: 228: 224: 220: 216: 212: 208: 204: 203: 202: 201: 195: 190: 186: 185: 184: 183: 182: 179: 177: 173: 169: 165: 160: 158: 154: 150: 147: 142: 138: 128: 126: 122: 118: 114: 110: 109:Alonzo Church 104: 102: 98: 94: 90: 86: 82: 76:Early history 73: 71: 67: 62: 59: 55: 53: 49: 39: 35: 31: 27: 23: 19: 636: 607: 602: 575: 571: 565: 553: 528: 524: 518: 502: 497: 489: 485: 477: 472: 464: 459: 440: 436: 423: 406: 398: 393: 377: 373: 357: 353: 337: 332: 316: 312: 268: 247: 234: 230: 226: 218: 211:Leonid Levin 206: 194:measure zero 188: 180: 161: 152: 148: 145: 134: 124: 116: 105: 100: 92: 79: 61:deliberately 60: 56: 52:D. H. Lehmer 44: 37: 17: 15: 501:R. Downey, 261:Yongge Wang 256:martingales 81:Émile Borel 665:Categories 397:E. Borel, 305:References 279:Randomness 93:collective 26:statistics 643:EMS Press 580:CiteSeerX 618:page 391 431:(1940). 418:page 260 388:page 166 273:See also 162:In 1966 30:sequence 645:, 2001 545:8931514 513:page 44 368:page 44 614:  582:  543:  509:  414:  384:  364:  344:  650:Video 541:S2CID 324:Notes 43:,..., 612:ISBN 507:ISBN 412:ISBN 382:ISBN 362:ISBN 342:ISBN 246:The 213:and 205:The 187:The 139:and 24:and 590:doi 533:doi 445:doi 146:any 72:. 32:of 667:: 641:, 635:, 588:. 576:69 574:. 539:. 527:. 441:46 439:. 435:. 178:. 127:. 596:. 592:: 547:. 535:: 529:5 453:. 447:: 235:n 231:n 227:n 219:n 149:N 117:N 47:n 45:X 41:1 38:X

Index

probability theory
statistics
sequence
random variables
D. H. Lehmer
Axiomatic probability theory
Bourbaki school
abuse of language
Émile Borel
Richard von Mises
algorithmic randomness
impossibility of a gambling system
Alonzo Church
recursive function
Church Turing Thesis
A. N. Kolmogorov
D. W. Loveland
Alexander Shen
Per Martin-Löf
algorithmic randomness
Kolmogorov complexity
universal Turing machine
measure zero
Leonid Levin
Gregory Chaitin
Kolmogorov complexity
Claus P. Schnorr
martingales
Yongge Wang
Randomness

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