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Prologue: What This Book Is About

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Fault-Tolerant Search Algorithms
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Abstract

The typical structure of a search problem is defined by a set of objects \(\mathcal{U}\), a family of tests \(\mathcal{T}\) which can be used to acquire information on the elements of \(\mathcal{U}\); a set of rules \(\mathcal{R}\) about the way the tests can be chosen or combined; and some performance measure \(\mathcal{M}\). The goal is to provide a strategy to select tests from \(\mathcal{T}\) according to the given rules \(\mathcal{R}\), in order to guarantee the correct identification of some initially unknown object in \(\mathcal{U}\), and optimize the given performance measure (e.g., worst case or average number of queries, time or space complexity, etc.).

For hateful in my eyes, even as the gates of Hades is that man that hideth one thing in his mind and sayeth another

Homer, Iliad IX. 312 313

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Notes

  1. 1.

    This concept will be precisely formalized later.

  2. 2.

    SIAM J. Appl. Math. 24 (1973).

  3. 3.

    Probl. Contr. Inform. Theory 2 (1973).

Bibliography

  1. R. Ahlswede, L. Bäumer, N. Cai, H. Aydinian, V. Blinovsky, C. Deppe, H. Mashurian, General Theory of Information Transfer and Combinatorics. Lecture Notes in Computer Science, vol. 4123 (Springer, Berlin, 2006)

    Google Scholar 

  2. R. Ahlswede, F. Cicalese, C. Deppe, Searching with lies under error cost constraints. Discrete Appl. Math. 156(9), 1444–1460 (2008)

    MathSciNet  MATH  Google Scholar 

  3. R. Ahlswede, F. Cicalese, C. Deppe, U. Vaccaro, Two batch search with lie cost. IEEE Trans. Inf. Theory 55(4), 1433–1439 (2009)

    Google Scholar 

  4. R. Ahlswede, I. Wegener, Search Problems (Wiley, Chichester, 1987)

    MATH  Google Scholar 

  5. M. Aigner, Searching with Lies. J. Comb. Theory Ser. A, 74, 43–56 (1995)

    MathSciNet  Google Scholar 

  6. M. Aigner, Combinatorial Search (Wiley, New York, 1988)

    MATH  Google Scholar 

  7. F. Albers, P. Damaschke, Delayed correction—binary search with errors made very simple but efficient. In Proc. CATS’98 Aust. Comput. Sci. Commun. 20(3), 97–105 (1998)

    Google Scholar 

  8. S. Albers, M. Charikar, M. Mitzenmacher, Delayed information and action in on-line algorithms, in Proceedings of 39th IEEE Symposium on Foundation of Computer Science (FOCS) (1998), pp. 71–81

    Google Scholar 

  9. N. Alon, R. Beigel, S. Kasif, S. Rudich, B. Sudakov, Learning a hidden matching. SIAM J. Comput. 33(2), 487–501 (2004)

    MathSciNet  MATH  Google Scholar 

  10. N. Alon, R. Hod, Optimal monotone encodings. IEEE Trans. Inf. Theory 55(3), 1343–1353 (2009)

    MathSciNet  Google Scholar 

  11. A. Ambainis, S.A. Bloch, D.L. Schweizer, Delayed binary search, or playing Twenty Questions with a procrastinator, in Proceedings of 10th AMC SIAM Symposium on Discrete Algorithms (SODA) (1999), pp. 844–845

    Google Scholar 

  12. D. Angluin, Queries and concept learning. Mach. Learn. 2, 319–342 (1988)

    Google Scholar 

  13. D. Angluin, Computational learning theory: survey and selected bibliography, in Proceedings of 24th ACM Symposium on the Theory of Computing (STOC) (1992), pp. 351–369

    Google Scholar 

  14. D. Angluin, P. Laird, Learning from noisy examples. Mach. Learn. 2, 343–370 (1988)

    Google Scholar 

  15. D. Angluin, P. Laird, Identifying k-CNF formulas from noisy example. DCS 478, Yale University, 1986

    Google Scholar 

  16. J. Aslam, A. Dhagat, Searching in the presence of linearly bounded errors, in Proceedings of 23rd ACM Symposium on the Theory of Computing (STOC) (1991), pp. 486–493

    Google Scholar 

  17. A. Bar-Noy, S. Kipnis, Designing broadcast algorithms in the postal model for message-passing systems. Math. Syst. Theory 27, 431–452 (1994)

    Google Scholar 

  18. A. Bar-Noy, S. Kipnis, B. Shieber, An optimal algorithm for computing census functions in message-passing systems. Parallel Process. Lett. 3(1), 19–23 (1993)

    Google Scholar 

  19. L.A. Bassalygo, Nonbinary error-correcting codes with one-time error-free feedback. Probl. Inf. Transm. 41(2), 125–129 (2005) [Translated from Problemy Peredachi Informatsii 2, 63–67 (2005)]

    Google Scholar 

  20. L.A. Bassalygo, V.A. Zinoviev, V.K. Leontiev, N.I. Feldman, Nonexistence of perfect codes for some composite alphabets. Problemy Peredachi Informatsii 11, 3–13 (1975) (in Russian) [English Translation: Probl. Inf. Transm. 11, 181–189 (1975)]

    Google Scholar 

  21. J.M. Berger, A note on error detecting codes for asymmetric channels. Inf. Control 4, 68–73 (1961)

    MATH  Google Scholar 

  22. E.R. Berlekamp, Block coding for the binary symmetric channel with noiseless, delayless feedback, in Error-Correcting Codes, ed. by H.B. Mann (Wiley, New York, 1968), pp. 61–68

    Google Scholar 

  23. E.R. Berlekamp, Algebraic Coding Theory (McGraw-Hill, New York, 1968)

    MATH  Google Scholar 

  24. D. Bertsekas, R. Gallager, Data Networks, 2nd edn. (Prentice Hall, Englewood Cliffs, 1992)

    MATH  Google Scholar 

  25. D. Blackwell, An analog of the minimax theorem for vector payoff. Pac. J. Math. 6, 1–8 (1956)

    Google Scholar 

  26. M. Blaum, Codes for Detecting and Correcting Unidirectional Errors (IEEE Computer Society, Los Alamitos, 1993)

    MATH  Google Scholar 

  27. A. Blikle, Three-valued predicates for software specification and validation. Fundam. Inf. 14, 387–410 (1991)

    MathSciNet  MATH  Google Scholar 

  28. A. Blum, On-line algorithms in machine learning, in Survey Talk given at Dagstuhl Workshop on On-line algorithms, June 1996

    Google Scholar 

  29. A.D. Booth, Inf. Control 1, 159–164 (1958)

    Google Scholar 

  30. R.S. Borgstrom, S. Rao Kosaraju, Comparison-based search in the presence of errors, in Proceedings of 25th ACM Symposium on the Theory of Computing (STOC) (1993), pp. 130–136

    Google Scholar 

  31. B. Bose, On systematic SEC-MUED codes, In Digest of Papers, 11th Annual International Symposium on Fault-Tolerant Computer (1981), pp. 265–267

    Google Scholar 

  32. B. Bose, T.R.N. Rao, Theory of Unidirectional error correcting/detecting codes. IEEE Trans. Comput. C-31(6), 520–530 (1982)

    MathSciNet  Google Scholar 

  33. B. Bose, D.K. Pradhan, Optimal Unidirectional error detecting/correcting codes. IEEE Trans. Comput. C-31(6), 564–568 (1982)

    Google Scholar 

  34. R.C. Bose, S.S. Shrikhande, E.T. Parker, Further results in the construction of mutually orthogonal Latin squares and the falsity of a conjecture of Euler. Can. J. Math. 12, 189–203 (1960)

    MathSciNet  MATH  Google Scholar 

  35. G.S. Brodal, R. Fagerberg, I. Finocchi, F. Grandoni, G.F. Italiano, A.G. Jørgensen, G. Moruz, T. Mølhave, Optimal resilient dynamic dictionaries, in Proceedings of the 15th European Symposium on Algorithms (ESA 2007). Lecture Notes in Computer Science, vol. 4698 (2007), pp. 347–358

    Google Scholar 

  36. A.E. Brouwer, T. Verhoeff, An updated table of minimum-distance bounds for binary linear codes. IEEE Trans. Inf. Theory 39, 662–677 (1993)

    MathSciNet  MATH  Google Scholar 

  37. A.E. Brouwer, J.B. Shearer, N.J.A. Sloane, W.D. Smith, A new table of constant weight codes. IEEE Trans. Inf. Theory 36, 1334–1380 (1990)

    MathSciNet  MATH  Google Scholar 

  38. P. Burcsi, F. Cicalese, G. Fici, Z. Lipták, Algorithms for jumbled pattern matching in strings. Int. J. Found. Comput. Sci. 23(2), 357–374 (2012)

    MATH  Google Scholar 

  39. N. Cesa-Bianchi, Y. Freund, D.P. Helmbold, D. Haussler, R. Schapire, M.K. Warmuth, How to use expert advice. J. ACM 44(3), 427–485 (1997)

    MathSciNet  MATH  Google Scholar 

  40. N. Cesa-Bianchi, Y. Freund, D. Helmbold, M.K. Warmuth, On-line prediction and conversion strategies. Mach. Learn. 25, 71–110 (1996)

    Google Scholar 

  41. C.C. Chang, Algebraic analysis of many valued logics. Trans. Am. Math. Soc. 88, 467–490 (1958)

    MATH  Google Scholar 

  42. C.C. Chang, A new proof of the completeness of Lukasiewicz’s axioms. Trans. Am. Math. Soc. 93, 74–80 (1959)

    MATH  Google Scholar 

  43. W.Y.C. Chen, J.S. Oliveira, Implication algebras and the Metropolis-Rota axioms for cubic lattices. J. Algebra 171, 383–396 (1995)

    MathSciNet  MATH  Google Scholar 

  44. Y. Cheng, D.Z. Du, New constructions of one- and two-stage pooling designs. J. Comput. Biol. 15(2), 195–205 (2008)

    MathSciNet  Google Scholar 

  45. Y. Cheng, D.Z. Du, G. Lin, On the upper bounds of the minimum number of rows of disjunct matrices. Optim. Lett. 3, 297–302 (2009)

    MathSciNet  MATH  Google Scholar 

  46. B.S. Chlebus, D.R. Kowalski, Almost optimal explicit selectors, in Proceedings of FCT 2005. Lecture Notes in Computer Science, vol. 3623 (2005), pp. 270–280

    MathSciNet  Google Scholar 

  47. M. Cheraghchi, Noise-resilient group testing: limitations and constructions, in Proceedings of FCT 2009. Lecture Notes in Computer Science, vol. 5699 (2009), pp. 62–73

    Google Scholar 

  48. M. Chrobak, L. Gasieniec, W. Rytter, Fast broadcasting and gossiping in radio networks. in Proceedings of FOCS 2000 (2000), pp. 575–581

    Google Scholar 

  49. F. Cicalese, The multi-interval Ulam-Rényi game, in Proceedings of FUN with Algorithms 2012. Lecture Notes in Computer Science, vol. 7288 (2012), pp. 69–80

    Google Scholar 

  50. F. Cicalese, D. Mundici, Optimal binary search with two unreliable tests and minimum adaptiveness, in Proceedings of the 7th European Symposium on Algorithms, ESA 1999. Lecture Notes in Computer Science, vol. 1643 (1999), pp. 257–266

    Google Scholar 

  51. F. Cicalese, D. Mundici, Recent developments of feedback coding and its relations with many-valued logic, in Proof, Computation and Agency - Logic at the Crossroads, ed. by J. van Benthem et al. Synthese Library, vol. 352, part 3 (Springer, Berlin, 2011), pp. 115-131

    Google Scholar 

  52. F. Cicalese, U. Vaccaro, An improved heuristic for Ulam-Rényi Game. Inf. Process.Lett. 73(3–4), 119–124 (2000)

    MathSciNet  MATH  Google Scholar 

  53. F. Cicalese, D. Mundici, U. Vaccaro, Least adaptive optimal search with unreliable tests, in Proceeding of SWAT 2000. Lecture Notes in Computer Science, vol. 1851 (2000), pp. 547–562

    MathSciNet  Google Scholar 

  54. F. Cicalese, D. Mundici, Perfect 2-fault tolerant search with minimum adaptiveness. Adv. Appl. Math. 25, 65–101 (2000)

    MathSciNet  MATH  Google Scholar 

  55. F. Cicalese, D. Mundici, Optimal coding with one asymmetric error: below the sphere packing bound, in Proceedings of COCOON 2000. Lecture Notes in Computer Science, vol. 1858 (2000), pp. 159–169

    MathSciNet  Google Scholar 

  56. F. Cicalese, C. Deppe, D. Mundici, q-ary Ulam-Rényi game with weighted constrained lies, in Proceedings of COCOON 2004. Lecture Notes in Computer Science, vol. 3106 (2004), pp. 82–91

    Google Scholar 

  57. F. Cicalese, q-ary searching with lies, in Proceedings of the 6th Italian Conference on Theoretical Computer Science (ICTCS ’98), Prato (1998), pp. 228–240

    Google Scholar 

  58. F. Cicalese, U. Vaccaro, Optimal strategies against a liar. Theor. Comput. Sci., 230, 167–193 (2000)

    MathSciNet  MATH  Google Scholar 

  59. F. Cicalese, U. Vaccaro, Coping with delays and time-outs in binary search procedures, in Proceedings of ISAAC 2000. Lecture Notes in Computer Science, vol. 1969 (2000), pp. 96–107

    MathSciNet  Google Scholar 

  60. F. Cicalese, D. Mundici, U. Vaccaro, Perfect, minimally adaptive, error-correcting searching strategies, in Proceedings of IEEE ISIT 2000 (2000), p. 377

    Google Scholar 

  61. F. Cicalese, D. Mundici, U. Vaccaro, Least adaptive optimal search with unreliable tests. Theor. Comput. Sci. 270(1–2), 877–893 (2001)

    MathSciNet  Google Scholar 

  62. F. Cicalese, P. Damaschke, L. Tansini, S. Werth, Overlaps help: improved bounds for group testing with interval queries. Discrete Appl. Math. 155(3), 288–299 (2007)

    MathSciNet  MATH  Google Scholar 

  63. F. Cicalese, J. Quitzau, 2-Stage fault tolerant interval group testing, in Proceedings of ISAAC 2007. Lecture Notes in Computer Science, vol. 4835 (2007), pp. 858–868

    Google Scholar 

  64. F. Cicalese, P. Damaschke, U. Vaccaro, Optimal group testing algorithms with interval queries and their application to splice site detection. Int. J. Bioinform. Res. Appl. 1(4), 363–388 (2005)

    Google Scholar 

  65. F. Cicalese, D. Mundici, Learning and the art of fault-tolerant guesswork, in Adaptivity and Learning - An Interdisciplinary Debate, ed. by R. Khün, R. Menzel, W. Menzel, U. Ratsch, M.M. Richter, I.O. Stamatescu (Springer, Berlin, 2003), pp. 115–140

    Google Scholar 

  66. F. Cicalese, D. Mundici, U. Vaccaro, Rota-Metropolis cubic logic and Ulam-Rényi games, in Algebraic Combinatorics and Computer Science—A Tribute to Giancarlo Rota, ed. by H. Crapo, D. Senato (Springer, Milano, 2001), pp. 197–244

    Google Scholar 

  67. F. Cicalese, T. Jacobs, E. Laber, C. Valentim, The binary identification problems for weighted trees. Theor. Comput. Sci. 459, 100–112 (2012)

    MathSciNet  MATH  Google Scholar 

  68. F. Cicalese, P.L. Erdős, Z. Lipták, A linear algorithm for string reconstruction in the reverse complement equivalence model. J. Discrete Algorithms 14, 37–54 (2012)

    MathSciNet  MATH  Google Scholar 

  69. F. Cicalese, E. Laber, The competitive evaluation complexity of monotone Boolean functions. J. ACM 58(3) (2011) [Article no. 9]

    Google Scholar 

  70. F. Cicalese, T. Jacobs, E. Laber, M. Molinaro, On the complexity of searching in trees and partially ordered structures. Theor. Comput. Sci. 412, 6879–6896 (2011)

    MathSciNet  MATH  Google Scholar 

  71. P. Burcsi, F. Cicalese, G. Fici, Z. Lipták, On approximate jumbled pattern matching in strings. Theory Comput. Syst. 50, 35–51 (2012)

    MathSciNet  MATH  Google Scholar 

  72. F. Cicalese, M. Milanič, Graphs of separability at most two. Discrete Appl. Math. 160, 685–696 (2012)

    MathSciNet  MATH  Google Scholar 

  73. F. Cicalese, T. Gagie, E. Laber, M. Milanič, Competitive Boolean function evaluation. Beyond monotonicity and the symmetric case. Discrete Appl. Math. 159, 1070–1078 (2011)

    MATH  Google Scholar 

  74. F. Cicalese, M. Milanič, Competitive evaluation of threshold functions in the priced information model. Ann. Oper. Res. 188(1), 111–132 (2011)

    MathSciNet  MATH  Google Scholar 

  75. F. Cicalese, U. Vaccaro, Superselectors: efficient constructions and applications, in Proceedings of the 18th Annual European Symposium on Algorithms (ESA 2010). Lecture Notes in Computer Science, vol. 6346 (Springer, Berlin, 2010), pp. 207–218

    Google Scholar 

  76. R. Cignoli, I.M.L. D’Ottaviano, D. Mundici, Algebraic Foundations of Many-Valued Reasoning. Trends in Logic, Studia Logica Library, vol. 7 (Kluwer, Dordrecht, 2000)

    Google Scholar 

  77. A.E.F. Clementi, A. Monti, R. Silvestri, Selective families, superimposed codes, and broadcasting on unknown radio networks, in Proceedings of Symposium on Discrete Algorithms (SODA’01) (2001), pp. 709–718

    Google Scholar 

  78. S.D. Constantin, T.R.N. Rao, On the theory of binary asymmetric error correcting codes. Inf. Control 40, 20–26 (1979)

    MathSciNet  MATH  Google Scholar 

  79. Z.A. Cox Jr., X. Sun, Y. Qiu, Optimal and heuristic search for a hidden object in one dimension. IEEE Int. Conf. Syst. Man Cybern. Hum. Inf. Technol. 2, 1252–1256 (1994)

    Google Scholar 

  80. D.E. Culler, R.M. Karp, D.A. Patterson, A. Sahay, E. Santos, K.E. Schauser, R. Subramonian, T. von Eicken, LogP: a practical model of parallel computation, in Communications of the ACM, November 1996

    Google Scholar 

  81. D. Culler, R. Karp, D. Patterson, A. Sahay, K.E. Schauser, E. Santos, R. Subramonian, T. von Eicken, LogP: toward a realistic model of parallel computation, in ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (1993), pp. 1–12

    Google Scholar 

  82. J. Czyzowicz, K. B. Lakshmanan, A. Pelc, Searching with a forbidden lie pattern in responses. Inf. Process. Lett. 37, 127–132 (1991)

    MathSciNet  MATH  Google Scholar 

  83. J. Czyzowicz, D. Mundici, A. Pelc, Ulam’s searching game with lies. J. Comb. Theory Ser. A 52, 62–76 (1989)

    MathSciNet  MATH  Google Scholar 

  84. J. Czyzowicz, K.B. Lakshmanan, A. Pelc, Searching with local constraints on error patterns. Eur. J. Comb. 15, 217–222 (1994)

    MathSciNet  MATH  Google Scholar 

  85. A. De Bonis, U. Vaccaro, Improved algorithms for group testing with inhibitors. Inf. Process. Lett. 66, 57–64 (1998)

    Google Scholar 

  86. A. De Bonis, New combinatorial structures with applications to efficient group testing with inhibitors. J. Comb. Optim. 15, 77–94 (2008)

    MathSciNet  MATH  Google Scholar 

  87. A. De Bonis, L. Gasieniec, U. Vaccaro, Optimal two-stage algorithms for group testing problems. SIAM J. Comput. 34(5), 1253–1270 (2005)

    MathSciNet  MATH  Google Scholar 

  88. P. Delsarte, Bounds for unrestricted codes, by linear programming. Philips Res. Rep. 27, 272–289 (1972)

    MathSciNet  MATH  Google Scholar 

  89. C. Deppe, Solution of Ulam’s searching game with three lies or an optimal adaptive strategy for binary three-error-correcting-codes. Technical Report No. 98–036, University of Bielefeld, Fakultät für Mathematik

    Google Scholar 

  90. C. Deppe, Coding with feedback and searching with lies, in Entropy, Search, Complexity, vol. 16, ed. by I. Csiszár, Gy.O.H. Katona, G. Tardos. Bolyai Society Mathematical Studies (János Bolyai Mathematical Society and Springer, 2007), pp. 27–70

    Google Scholar 

  91. A. De Santis, G. Markowsky, M. Wegman, Learning probabilistic prediction functions, in Proceedings of 29th IEEE Symposium on Foundation of Computer Science (FOCS) (1988), pp. 110–119

    Google Scholar 

  92. A. Dhagat, P. Gács, P. Winkler, On playing “Twenty Questions” with a liar, in Proceedings of 3rd Annual ACM SIAM Symposium on Discrete Algorithms (SODA 92) (1992), pp. 16–22

    Google Scholar 

  93. R.L. Dobrushin, Information transmission in a channel with feedback. Theory Probab. Appl. 34, 367–383 (1958) [Reprinted in: Key Papers in the Development of Information Theory, ed. by D. Slepian (IEEE, New York, 1974)]

    Google Scholar 

  94. D.Z. Du, F.K. Hwang, Combinatorial Group Testing and its Applications. Series on Applied Mathematics, vol. 12, 2nd edn. (World Scientific, Singapore, 2000)

    Google Scholar 

  95. D.Z. Du, F.K. Hwang, Pooling Design and Nonadaptive Group Testing (World Scientific, Singapore, 2006)

    Google Scholar 

  96. A.I. Dumey, Comput. Autom. 5(12), 6–9 (1956)

    Google Scholar 

  97. I. Dumitriu, J. Spencer, The liar game over an arbitrary channel. Combinatorica 25, 537–559 (2005)

    MathSciNet  MATH  Google Scholar 

  98. I. Dumitriu, J. Spencer, The two-batch liar game over an arbitrary channel. SIAM J. Discrete Math. 19, 1056–1064 (2006)

    MathSciNet  MATH  Google Scholar 

  99. A.C. Dusseau, D.E. Culler, K.E. Schauser, R. Martin, Fast Parallel Sorting under LogP: Experience with the CM-5, In IEEE Transaction on Parallel and Distributed Systems, August 1996

    Google Scholar 

  100. A.G. D’yachkov, V.V. Rykov, Bounds of the length of disjunct codes. Probl. Control Inf. Theory 11, 7–13 (1982)

    Google Scholar 

  101. A.G. D’yachkov, V.V. Rykov, A.M. Rashad, Superimposed distance codes. Probl. Control Inf. Theory 18, 237–250 (1989)

    Google Scholar 

  102. P. Elias, IBM F. Res. Dev. 3, 346–353 (1958)

    Google Scholar 

  103. M.A. Epstein, Algebraic decoding for a binary erasure channel. IRE Natl. Conv. Rec. 6(4), 56–69 (1958)

    Google Scholar 

  104. M. Farach, S. Kannan, E. Knill, S. Muthukrishnan, Group testing problems with sequences in experimental molecular biology, in Proceedings of the Compression and Complexity of Sequences 1997, ed. by B. Carpentieri, A. De Santis, U. Vaccaro, J. Storer (1997), pp. 357–367

    Google Scholar 

  105. M. Feder, N. Merhav, M. Gutman, Universal prediction of individual sequences. IEEE Trans. Inf. Theory 38, 1258–1270 (1992)

    MathSciNet  MATH  Google Scholar 

  106. U. Feige, D. Peleg, P. Raghavan, E. Upfal, Computing with unreliable information, in Proceedings of ACM Symposium on Theory of Computing (STOC) (1990), pp. 128–137

    Google Scholar 

  107. I. Finocchi, G.F. Italiano, Sorting and searching in faulty memories. Algorithmica 52, 309–332 (2008)

    MathSciNet  MATH  Google Scholar 

  108. I. Finocchi, F. Grandoni, G.F. Italiano, Optimal resilient sorting and searching in the presence of dynamic memory faults, in Proceedings of ICALP’06. Lecture Notes in Computer Science, vol. 4051 (2006), pp. 286–298

    Google Scholar 

  109. I. Finocchi, F. Grandoni, G.F. Italiano, Resilient search trees, in Proceedings of the ACM-SIAM Symposium on Discrete Algorithm (SODA’07) (2007), pp. 547–555

    Google Scholar 

  110. Y. Freund, Predicting a binary sequence almost as well as the optimal biased coin, in Proceedings of the 9th Annual Conference on Computational Learning Theory (1996), pp. 89–98

    Google Scholar 

  111. C.V. Freiman, Optimal error detection codes for completely asymmetric binary channel. Inf. Control 5, 64–71 (1962)

    MathSciNet  MATH  Google Scholar 

  112. A.C. Gilbert, M.A. Iwen, M.J. Strauss, Group testing and sparse signal recovery, in Proceedings of the 42nd Asilomar Conference on Signals, Systems, and Computers (2008), pp. 1059–1063

    Google Scholar 

  113. M.J.E. Golay, Notes on digital coding. Proc. IEEE 37, 657 (1949)

    Google Scholar 

  114. M. Golin, A. Schuster, Optimal point-to-point broadcast algorithms via lopsided trees. Discrete Appl. Math. 93, 233–263 (1999)

    MathSciNet  MATH  Google Scholar 

  115. W. Guzicki, Ulam’s searching game with two lies. J. Comb. Theory Ser. A 54, 1–19 (1990)

    MathSciNet  MATH  Google Scholar 

  116. R.W. Hamming, Error detecting and error correcting codes. Bell Syst. Tech. J. 29, 147–160 (1950)

    MathSciNet  Google Scholar 

  117. R. Hähnle, W. Kernig, Verification of switch level design with many-valued logic, in Proceedings of LPAR’93. Lecture Notes in Artificial Intelligence, vol. 698 (1993), pp. 158–169

    Google Scholar 

  118. R. Hassin, M. Henig, Monotonicity and efficient computation of optimal dichotomous search. Discrete Appl. Math. 46, 221–234 (1993)

    MathSciNet  MATH  Google Scholar 

  119. R. Hill, Searching with lies, in Surveys in Combinatorics, ed. by P. Rowlinson (Cambridge University Press, Cambridge, 1995), pp. 41–70

    Google Scholar 

  120. R. Hill, J. Karim, E.R. Berlekamp, The solution of a problem of Ulam on searching with lies, in Proceedings of IEEE ISIT 1998, Cambridge (1998), p. 244

    Google Scholar 

  121. R. Hill, J.P. Karim, Searching with lies: the Ulam problem. Discrete Math. 106/107, 273–283 (1992)

    Google Scholar 

  122. K. Hinderer, M. Stieglitz, On polychotomous search problems. Eur. J. Oper. Res. 73, 279–294 (1994)

    MATH  Google Scholar 

  123. Y.-W. Hong, A. Scaglione, On multiple access for distributed dependent sources: a content-based group testing approach, in Proceedings of the IEEE Information Theory Workshop, 2004 (ITW 2004) (2004), pp. 298–303

    Google Scholar 

  124. Y.-W. Hong, A. Scaglione, Group testing for sensor networks: the value of asking the right questions, in Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers (COSSAC 2004), vol. 2 (2004), pp. 1297–1301

    Google Scholar 

  125. Y.-W. Hong, A. Scaglione, Generalized group testing for retrieving distributed information, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), vol. 3 (2005), pp. 681–684

    Google Scholar 

  126. D.A. Huffman, Method for the construction of minimum redundancy codes. Proc. IRE 40, 1098–1101 (1952)

    Google Scholar 

  127. P. Indyk, H.Q. Ngo, A. Rudra, Efficiently decodable non-adaptive group testing, in Proceedings of 21st Annual Symposium on Discrete Algorithms (SODA) (2010), pp. 1126–1142

    Google Scholar 

  128. D. Innes, Searching with a lie using only comparison questions (unpublished manuscript)

    Google Scholar 

  129. A.G. Jørgensen, G. Moruz, T. Mølhave, Priority queues resilient to memory faults, in Proceedings of the 10th Workshop on Algorithms and Data Structures (WADS’07). Lecture Notes in Computer Science, vol. 4619 (2007), pp. 127–138

    Google Scholar 

  130. R. Karp, ISIT’98 plenary lecture report: variations on the theme of “Twenty Questions”. IEEE Inf. Theory Soc. Newslett. 49(1), 1–5 (1999)

    Google Scholar 

  131. G. Katona, Combinatorial search problems, in A Survey of Combinatorial Theory (North-Holland, Amsterdam, 1966), pp. 285–308

    Google Scholar 

  132. M. Kearns, M. Li, Learning in presence of malicious errors, in Proceedings of 20th ACM Symposium on Theory of Computing (STOC) (1988), pp. 267–280

    Google Scholar 

  133. C. Kenyon, A. Yao, On evaluating Boolean function with unreliable tests, Int. J. Found. Comput. Sci. 1(1), 1–10 (1990)

    MathSciNet  MATH  Google Scholar 

  134. E. Knill, Lower bounds for identifying subset members with subset queries, in Proceedings of 6th ACM SIAM Symposium on Discrete Algorithms (SODA) (1995), pp. 369–377

    Google Scholar 

  135. D. Knuth, Searching and Sorting, The Art of Computer Programming, vol. 3 (Addison-Wesley, Reading, 1998)

    Google Scholar 

  136. T. Kopelowitz, N. Talmon, Selection in the presence of memory faults, with applications to in-place resilient sorting. ArXiv (2012)

    Google Scholar 

  137. H.T. Kung, Synchronized and asynchronous parallel algorithms for multiprocessors, in Algorithms and Complexity: New Directions and Recent Results, ed. by J.F. Traub (Academic, London, 1979), pp. 153–200

    Google Scholar 

  138. E.L. Lawer, S. Sarkissian, An algorithm for “Ulam’s Game” and its application to error correcting codes. Inf. Process. Lett. 56, 89–93 (1995)

    Google Scholar 

  139. Y. Li, M.T. Thai, Z. Liu, W. Wu, Protein-protein interaction and group testing in bipartite graphs. Intl. J. Bioinform. Res. Appl. 1(6), 414–419 (2005)

    Google Scholar 

  140. N. Linial, M. Sacks, Every poset has a central element. J. Comb. Theory Ser. A 40, 195–210 (1985)

    MATH  Google Scholar 

  141. N. Linial, M. Sacks, Searching ordered structures. J. Algorithms 6, 86–103 (1985)

    MathSciNet  MATH  Google Scholar 

  142. N. Littlestone, Learning quickly when irrelevant attributes abound: a new linear-threshold algorithm. Mach. Learn. 2, 285–318 (1988)

    Google Scholar 

  143. N. Littlestone, M.K. Warmuth, The weighted majority algorithm. Inf. Comput. 108(2), 212–261 (1994)

    MathSciNet  MATH  Google Scholar 

  144. J. Lukasiewicz, O Logice Trówartosciowej. Ruch Filozoficzny 5, 170–171 (1920) [English Translation: J. Lukasiewicz, On three-valued logic, in Selected Works (North-Holland, Amsterdam, 1970), pp. 87–88]

    Google Scholar 

  145. F.J. MacWilliams, N.J.A. Sloane, The Theory of Error-Correcting Codes (North-Holland, Amsterdam, 1977)

    MATH  Google Scholar 

  146. A. Malinowski, k-ary searching with a lie. Ars Comb. 37, 301–308 (1994)

    Google Scholar 

  147. J.J. Metzner, Improvements in block-retransmission schemes. IEEE Trans. Commun. 27(2), 525–532 (1979)

    Google Scholar 

  148. R.J. McEliece, E.R. Rodemich, H.C. Rumsey, L.R. Welch, New upper bounds on the rate of a code via the Delsarte-MacWilliams inequalities. IEEE Trans. Inf. Theory 23, 157–166 (1977)

    MathSciNet  MATH  Google Scholar 

  149. E.F. Moore, C.E. Shannon, Reliable circuits using less reliable relays, part I. J. Franklin Inst. 262, 191–208 (1956)

    MathSciNet  Google Scholar 

  150. E.F. Moore, C.E. Shannon, Reliable circuits using less reliable relays, part II. J. Franklin Inst. 262, 281–297 (1956)

    MathSciNet  Google Scholar 

  151. D. Mundici, Ulam’s game, Łukasiewicz logic and AF C-algebras. Fundam. Inf. 18, 151–161 (1993)

    MathSciNet  MATH  Google Scholar 

  152. D. Mundici, The C -algebras of three-valued logic, in Proceedings of Logic Colloquium 1988, Padova, ed. by R. Ferro, C. Bonotti, S. Valentini, A. Zanardo. Studies in Logic and the Foundations of Mathematics (North-Holland, Amsterdam, 1989), pp. 61–77

    Google Scholar 

  153. D. Mundici, The logic of Ulam’s game with lies, in Knowledge, Belief and Strategic Interaction, ed. by C. Bicchieri, M.L. Dalla Chiara, Cambridge Studies in Probability, Induction, and Decision Theory (Cambridge University Press, 1992), pp. 275–284

    Google Scholar 

  154. D. Mundici, Fault-tolerance and Rota-Metropolis cubic logic, in Paraconsistency, the Logical Way to the Inconsistented, ed. by W.A. Carnielli, M.E. Coniglio, I.M.L. D’Ottaviano. Lecture Notes in Pure and Applied Mathematics, vol. 228 (Marcel Dekker, New York, 2002), pp. 397–410

    Google Scholar 

  155. D. Mundici, A. Trombetta, Optimal comparison strategies in Ulam’s searching game with two errors. Theor. Comput. Sci. 182, 217–232 (1997)

    MathSciNet  MATH  Google Scholar 

  156. S. Muthukrishnan, On optimal strategies for searching in presence of errors, in Proceedings of 5th ACM-SIAM Symposium on Discrete Algorithms (SODA’94) (1994), pp. 680–689

    Google Scholar 

  157. A. Negro, M. Sereno, Ulam’s Searching game with three lies. Adv. Appl. Math. 13, 404–428 (1992)

    MathSciNet  MATH  Google Scholar 

  158. M.B. Or, A. Hassidim, The Bayesian learner is optimal for noisy binary search (and pretty good for quantum as well), in Proceedings of 49th Annual IEEE Symposium on Foundations of Computer Science (FOCS’08) (2008), pp. 221–230

    Google Scholar 

  159. A. Pedrotti, Reliable RAM computation in the presence of noise. Ph.D. thesis, Scuola Normale Superiore, Pisa, 1998

    Google Scholar 

  160. A. Pelc, Searching games with errors—fifty years of coping with liars. Theor. Comput. Sci. 270(1–2), 71–109 (2002)

    MathSciNet  MATH  Google Scholar 

  161. A. Pelc, Detecting errors in searching games. J. Comb. Theory Ser. A 51, 43–54 (1989)

    MathSciNet  MATH  Google Scholar 

  162. A. Pelc, Solution of Ulam’s problem on searching with a lie. J. Comb. Theory Ser. A 44, 129–142 (1987)

    MathSciNet  MATH  Google Scholar 

  163. A. Pelc, Lie patterns in search procedures. Theor. Comput. Sci. 47, 61–69 (1986)

    MathSciNet  MATH  Google Scholar 

  164. A. Pelc, Weakly adaptive comparison searching. Theor. Comput. Sci. 66, 105–111 (1989)

    MathSciNet  MATH  Google Scholar 

  165. A. Pelc, Detecting a counterfeit coin with unreliable weighing. Ars Comb. 27, 185–202 (1989)

    MathSciNet  Google Scholar 

  166. A. Pelc, Searching with permanently faulty tests. Ars Comb. 38, 65–76 (1994)

    Google Scholar 

  167. A. Pelc, Searching with known error probability. Theor. Comput. Sci.63, 185–202 (1989)

    MathSciNet  MATH  Google Scholar 

  168. A. Pelc, Prefix search with a lie. J. Comb. Theory Ser. A 48, 165–173 (1988)

    MathSciNet  MATH  Google Scholar 

  169. A. Pelc, Coding with bounded error fraction. Ars Comb. 24, 17–22 (1987)

    MathSciNet  MATH  Google Scholar 

  170. W.W. Peterson, IBM J. Res. Dev. 1, 130–146 (1957)

    Google Scholar 

  171. W.W. Peterson, Encoding and error-correction procedures for Bose-Chaudhuri codes. IEEE Trans. Inf. Theory 6, 459–470 (1960)

    Google Scholar 

  172. W.W. Peterson, E.J. Weldon, Error-Correcting Codes (MIT, Cambridge, 1971)

    Google Scholar 

  173. P.A. Pevzner, Computational Molecular Biology: An Algorithmic Approach (MIT, Cambridge, 2000)

    Google Scholar 

  174. C. Picard, Theory of Questionnaires (Gauthier-Villars, Paris, 1965)

    Google Scholar 

  175. J.R. Pierce, Optical channels: practical limits with photon counting. IEEE Trans. Comm. COM-26, 1819–1821 (1978)

    MathSciNet  Google Scholar 

  176. N. Pippenger, On networks of noisy gates, in Proceedings of 26th IEEE Symposium on Foundation of Computer Science (FOCS) (1985), pp. 30–38

    Google Scholar 

  177. E. Porat, A. Rothschild, Explicit non-adaptive combinatorial group testing schemes. IEEE Trans. Inf. Theory 57(12), 7982–7989 (2011)

    MathSciNet  Google Scholar 

  178. E. Post, Introduction to a general theory of elementary propositions. Am. J. Math. 43, 163–185 (1921)

    MathSciNet  MATH  Google Scholar 

  179. Y. Tohma, Coding Techniques in Fault-tolerant, self-checking, and fail-safe circuits, in Fault-Tolerant Computing, Theory and techniques, ed. by D.K. Pradhan (Prentice-Hall, Englewood, 1986), pp. 336–411

    Google Scholar 

  180. B. Ravikumar, K. B. Lakshmanan, Coping with known patterns of lies in a search game. Theor. Comput. Sci. 33, 85–94 (1984)

    MathSciNet  MATH  Google Scholar 

  181. I.S. Reed, G. Solomon, Polynomial codes over certain finite fields. SIAM J. Appl. Math. 8, 300–304 (1960)

    MathSciNet  MATH  Google Scholar 

  182. A. Rényi, Napló az információelméletről (Gondolat, Budapest, 1976) [English translation: A Diary on Information Theory (Wiley, New York, 1984)]

    Google Scholar 

  183. A. Rényi, On a problem of information theory. MTA Mat. Kut. Int. Kozl. 6B, 505–516 (1961)

    Google Scholar 

  184. A. Rényi, Lecture Notes on the Theory of Search. University of North Carolina at Chapel Hill, Institute of Statistics Mimeo Series No. 600.7 (1969)

    Google Scholar 

  185. R.L. Rivest, A.R. Meyer, D.J. Kleitman, K. Winklmann, J. Spencer, Coping with errors in binary search procedures. J. Comput. Syst. Sci. 20, 396–404 (1980)

    MATH  Google Scholar 

  186. H. Robbins, Asymptotically subminimax solutions of compound statistical decision problems, in Proceedings of 2nd Berkeley Symposium on Mathematical Statistics and Probability (1951), pp. 131–148

    Google Scholar 

  187. G.-C. Rota, N. Metropolis, Combinatorial structure of the faces of the n-cube. SIAM J. Appl. Math. 35, 689–694 (1978)

    MathSciNet  MATH  Google Scholar 

  188. M. Ruszinkó, On the upper bound of the size of the r-cover-free families. J. Comb. Theory Ser. A 66, 302–310 (1994)

    MATH  Google Scholar 

  189. M. Sereno, Binary search with errors and variable cost queries. Inf. Process. Lett. 68(5), 261–270 (1998)

    MathSciNet  Google Scholar 

  190. C.E. Shannon, A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423, 623–658 (1948) [Reprinted in: A Mathematical Theory of Communication, ed. by C.E. Shannon, W. Weaver (University of Illinois Press, Urbana, 1963)]

    Google Scholar 

  191. C.E. Shannon, Communication in the presence of noise. Proc. IEEE 37, 10–21 (1949)

    MathSciNet  Google Scholar 

  192. C.E. Shannon, Zero-capacity of noisy channels. IEEE Trans. Inf. Theory 2, 8–19 (1956)

    MathSciNet  Google Scholar 

  193. J. Shtarkov, Universal sequential coding of single measures. Probl. Inf. Transm. 23(3), 3–17 (1987)

    MathSciNet  Google Scholar 

  194. R.C. Singleton, Maximum distance q-nary codes. IEEE Trans. Inf. Theory 10, 116–118 (1964)

    MathSciNet  MATH  Google Scholar 

  195. B. Sklar, Digital Communications: Fundamentals and Applications (Prentice-Hall, Englewood, 2001)

    Google Scholar 

  196. J. Spencer, Balancing games. J. Comb. Theory Ser. B 23, 68–74 (1977)

    MATH  Google Scholar 

  197. J. Spencer, Guess a number with lying. Math. Mag. 57, 105–108 (1984)

    MathSciNet  MATH  Google Scholar 

  198. J. Spencer, Ulam’s searching game with a fixed number of lies. Theor. Comput. Sci. 95, 307–321 (1992)

    MATH  Google Scholar 

  199. J. Spencer, P. Winkler, Three thresholds for a liar. Comb. Probab. Comput. 1, 81–93 (1992)

    MathSciNet  MATH  Google Scholar 

  200. T.M. Thompson, From Error-Correcting Codes through Sphere Packings to Simple Groups. Carus Mathematical Monograph, vol. 21 (Mathematical Association of America, Washington, 1983)

    Google Scholar 

  201. A. Tietäväinen, On the nonexistence of perfect codes over finite fields. SIAM J. Appl. Math. 24, 88–96 (1973)

    MathSciNet  MATH  Google Scholar 

  202. S.M. Ulam, Adventures of a Mathematician (Scribner’s, New York, 1976)

    MATH  Google Scholar 

  203. L.G. Valiant, A theory of the learnable. Commun. ACM 27, 1134–1142 (1984)

    MATH  Google Scholar 

  204. L. Valiant, Learning disjunctions of conjunctions, in Proceedings of 9th IJCAI (1985), pp. 560–566

    Google Scholar 

  205. J.H. van Lint, Introduction to Coding Theory (Springer, Berlin, 1982)

    MATH  Google Scholar 

  206. J.H. van Lint, R.M. Wilson, A Course in Combinatorics (Cambridge University Press, Cambridge, 1992)

    MATH  Google Scholar 

  207. J. von Neumann, Probabilistic logics and the synthesis of reliable organisms from unreliable components, in Automata Studies, ed. by C. Shannon, J. McCarthy (Princeton University Press, Princeton, 1956), pp. 43–98

    Google Scholar 

  208. V. Vovk, Aggregating strategies, in Proceedings of 3rd Annual Workshop on Computational Learning Theory (1990), pp. 371–383

    Google Scholar 

  209. S.B. Wicker, V.K. Bhargava (ed.), Reed-Solomon Codes and Their Applications (Wiley, London, 1999)

    Google Scholar 

  210. S. Winograd, F.D. Cowan, Reliable Computation in the Presence of Noise (MIT, Cambridge, 1963)

    MATH  Google Scholar 

  211. W. Wu, Y. Li, C.H. Huang, D.Z. Du, Molecular biology and pooling design, in Data Mining in Biomedicine, vol. 7. Springer Optimization and Its Applications (Springer, Berlin, 2008), pp. 133–139

    Google Scholar 

  212. G. Xu, S.H. Sze, C.P. Liu, P.A. Pevzner, N. Arnheim, Gene hunting without sequencing genomic clones: finding exon boundaries in cDNAs. Genomics 47(2), 171–179 (1998)

    Google Scholar 

  213. A.M. Yaglom, I.M. Yaglom, Verojatnost’ i Informacija (Nakua, Moscow, 1957) [French Translation: Probabilité et Information (Dunod, Paris, 1969)]

    MATH  Google Scholar 

  214. S.A. Zenios, L.M. Wein, Pooled testing for HIV prevalence estimation: exploiting the dilution effect. Stat. Med. 17, 1446–1467 (1998)

    Google Scholar 

  215. V.A. Zinoviev, V.K. Leontiev, The non-existence of perfect codes over Galois fields. Probl. Contr. Inf. Theory 2, 123–132 (1973)

    Google Scholar 

  216. V.A. Zinoviev, G.L. Katsman, Universal code families. Inf. Theory Coding Theory 29(2), 95–100 (1993)

    Google Scholar 

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Cicalese, F. (2013). Prologue: What This Book Is About. In: Fault-Tolerant Search Algorithms. Monographs in Theoretical Computer Science. An EATCS Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17327-1_1

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