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Discrete Mathematics and Game Theory PDF

349 Pages·1999·8.473 MB·English
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DISCRETE MATHEMATICS AND GAMETHEORY THEORY AND DECISION LIBRARY General Editors: W. Leinfellner (Vienna) and G. Eberlein (Munich) SeriesA: PhilosophyandMethodologyoftheSocialSciences SeriesB: MathematicalandStatisticalMethods SeriesC: GameTheory.MathematicalProgrammingandOperationsResearch SeriesD: SystemTheory,KnowledgeEngineeringan ProblemSolving SERIES C: GAMETHEORY, MATHEMATICALPROGRAMMING ANDOPERATIONSRESEARCH VOLUME22 Editor: S. H. Tijs (University ofTilburg); EditorialBoard: E.E.C. van Damme (Tilburg), H. Keiding (Copenhagen), J.-F. Mertens (Louvain-la-Neuve), H. Moulin (Durham), S. Muto (Tokyo University), T. Parthasarathy (New Delhi), B. Peleg (Jerusalem), H. Peters (Maastricht), T. E. S. Raghavan (Chicago), J. Rosenmiiller (Bielefeld), A. Roth (Pittsburgh), D. Schmeidler (Tel-Aviv), R. Selten (Bonn),W.Thomson(Rochester, NY). Scope: Particularattention is paid in this series to game theory and operations research, their formal aspectsand theirapplications to economic, political and social sciencesas wellas tosocio-biology. It will encourage high standards in the application ofgame-theoretical methods to individualand social decisionmaking. The titlespublishedinthisseriesarelistedattheendofthisvolume. DISCRETE MATHEMATICS AND GAME THEORY by Guillermo Owen Naval Postgraduate School, Monterey, California, U.S.A. SPRINGER SCIENCE+BUSINESS MEDIA, B.V. A C.I.P. Catalogue record for this book is available from the Library of Congress. ISBN 978-1-4613-7266-0 ISBN 978-1-4615-4991-8 (eBook) DOI 10.1007/978-1-4615-4991-8 Printed on acid-free paper AlI Rights Reserved © 1999 Springer Science+Business Media Dordrecht OriginaIly published by Kluwer Academic Publishers in 1999 Softcover reprint ofthe hardcover Ist edition 1999 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permis sion from the copyright owner. TableofContents ChapterI. VectorsandMatrices 1. AlgebraicOperations 1 2.RowOperationsandtheSolutionofSystemsofLinearEquations 7 3. SolutionofGeneral mxnSystemsofEquations 15 ChapterII.LinearProgramming 27 1. LinearPrograms 27 2. TheSimplexAlgorithm: SlackVariables 37 3. TheSimplexTableau 41 4. TheSimplexAlgorithm: Objectives 47 5. TheSimplexAlgorithm: ChoiceofPivots 48 6. TheSimplexAlgorithm: StageI. 55 7. TheSimplexAlgorithm: ProofofConvergence 58 8. EquationConstraints 66 9. DegeneracyProcedures 70 10. SomePracticalComments 74 11.Duality 77 12. TransportationProblems 92 13. AssignmentProblems 102 ChapterIII.TheTheoryofProbability 113 1. Probabilities 113 2. DiscreteProbabilitySpaces 115 3. ConditionalProbability. 123 4. CompoundExperiments 126 5. Bayes'Formula 131 6. RepetitionofSimpleExperiments;TheBinomialDistribution 138 7.DrawingswithandwithoutReplacement 141 8. RandomVariables 145 9. ExpectedValues. MeansandVariances 151 10.Rulesfor ComputingtheMeanandVariance 155 11.TwoImportantTheorems 158 12. MarkovChains 167 13. RegularandAbsorbingMarkovChains 172 ChapterIV. TheTheoryofGames 181 1. Games: ExtensiveandNormal Form 181 2. SaddlePoints 185 3. MixedStrategies 192 4. Solutionof2x2Games 199 5. 2xnandmx2Games 203 6. SolutionsbyLinearProgramming 209 7. SolutionofGamesbyFictitiousPlay 218 8. ThevonNeumannModelofanExpandingEconomy 222 9. ExistenceofanEquilibriumExpansionRate 228 10. Two-PersonNon-Zero-SumGames 236 11.EvolutionaryStableSystems 245 ChapterV. CooperativeGames 253 1. n-PersonGames 253 2. TheCore 256 3. TheShapleyValue 260 4. VotingStructures 266 ChapterVI.DynamicProgramming 271 1. ThePrincipleofMaximality 271 2. TheFixed-ChargeTransportationProblem 279 3. Inventories 287 4. StochasticInventorySystems 294 ChapterVIl. GraphsandNetworks 303 1.Introduction 303 2. CriticalPathAnalysis 304 3. TheShortestPaththroughaNetwork 314 4. Minimal SpanningTrees 319 5. TheMaximalFlowinaNetwork 324 vi I. VECTORS AND MATRICES 1. ALGEBRAIC OPERATIONS We assume thatthe reader is already familiar with the ordinary algebraofvectors andmatrices. We givethe basics below. Amatrix is arectangulararrayofnumbers, arrangedin rows and columns. Ifithas mrows and ncolumns, we saythat it is an mxn matrix. Forexample, 4 1 2 0 A= 2 -4 5 I 3 0 -1 2 is a3x4 matrix, while 6 3 B= 7 4 8 -3 -2 5 is a4x2 matrix. Thenumbers thatmake up the matrix are calledentries. We willfrequently use letters with two subscriptsto representthese entries. Thus, would be the entry in aij the ithrow andjthcolumn ofmatrix A, b would be the entry inthe 3'd row and pI 31 columnofB, etc. Matrices are in some sense ageneralizationofthe conceptofnumber. Thus itis not surprisingthatcertainoperations canbe carriedoutonmatrices, similarto the arithmetic operations. These include addition andmultiplicationofmatrices, and scalarmultiplication. There is also the operationoftransposition. Transposition. IfAis an mxn matrix, then the transpose ofAis an nxm matrix, B, defined by We will use AI to denote the transpose ofA. Forexample, l I D 1.1.1 7 1 -4 If A= 1 3 then 3 2 -4 2 Addition ofmatrices. IfAand Bare two mxn matrices (notethe two matriceshave the same mandthe same n) then theirsum, A+B, is also an mxn matrix, C, defmed by = b Cij aij+ ij. Thus, 3 4 -1 + 2 -6 3 5 -2 2 1 -3 0 I 5 2 2 6 -1 2 Scalar multiplication. IfAis an mxn matrix, ands is anumber. Thenthe product, sA, is also an mxn matrix, D, definedby 1.1.2 dij =sajj Thus 4 3 4 -1 12 16 -4 I 1 -3 0 I 4 -12 0 Note thatinthis context, the numbers (whichmultiplies the matrix) is frequently calledascalar. Multiplicationofmatrices. LetAbe an mxn matrix, and letBbe an nxpmatrix. Thenthe productAB is an mxpmatrix, Q, defined by 1.1.3 2 Thus, T I l 1 5 6+4 30+8 10 38 2 4 4 8 2+16 10+32 18 42 -1 3 -1+12 -5+24 11 19 Note that AB is notnecessarilyequalto BA. Infact, itmay be thatone ofthese products exists while the otherone does not; evenifthey bothexist, moreover, they neednot be equal. I.l.l. Rules for operations on matrices Thefollowing hold for the operations: 1. IfAand Bare bothmxn matrices, then 2. Forany A, 3. IfAandBare both mxn matrices, then A+B=B+A 4. IfA, B, andCare three mxn matrices, then (A+B)+ C= A+(B +C) 5. IfAandBare mxn matrices, ands is ascalar, then s(A+B) =sA+sB 6. IfAis amatrix and rands are scalars, then (r+s)A = rA +sA. 3 and (rs)A =r(sA) 7. Forany givenmand n, there exists an mxn matrix, 0, suchthat, ifAis also mxn, then A+O = A. 8. IfAis mxn, Bisnxp, and Cispxq, then (AB)C = A(BC) 9. IfAis mxn, Bisnxp, ands is ascalar, then (sA)B =A(sB) =s(AB) 10. IfAand Bare both mxn n, and Cisnxp, then (A+B) C= AC +BC 11. IfAis mxn, and BandCare bothnxp, then A(B +C)= AB +AC 12. Foranyn, there exists andnxn matrix, I, suchthat, ifAis any mxn matrix, then AI=A and, ifBis any nxpmatrix, then ID=B. 13. IfAis mxn, and Bisnxp, then (AB)' = B'A' Thematrix 0, referred to in (7) above, is simply an mxn matrix, all ofwhose entries are o. Itis known as the additive identity, orzero matrix. Note thatfor any A, we candefine the matrix -Aas the product(-I)A. Itis easyto checkthat 4

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