The theory of evolution strategies with 9 tables
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| Sprache: | English |
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Berlin [u.a.]
Springer
2001
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| Schriftenreihe: | Natural computing series
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| 100 | 1 | |a Beyer, Hans-Georg |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a The theory of evolution strategies |b with 9 tables |c Hans-Georg Beyer |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2001 | |
| 300 | |a XIX, 380 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Natural computing series | |
| 650 | 4 | |a Evolutionsstrategie | |
| 650 | 4 | |a Computer algorithms | |
| 650 | 4 | |a Evolutionary programming (Computer science) | |
| 650 | 0 | 7 | |a Evolutionsstrategie |0 (DE-588)4015930-9 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Evolutionsstrategie |0 (DE-588)4015930-9 |D s |
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| 856 | 4 | 2 | |m HEBIS Datenaustausch Darmstadt |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009328407&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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Datensatz im Suchindex
| DE-19_call_number | 1004/QH 252 B573 |
|---|---|
| DE-19_location | 70 |
| DE-BY-TUM_call_number | 0001 05.2001 A 123 |
| DE-BY-TUM_katkey | 1200339 |
| DE-BY-TUM_location | Mag |
| DE-BY-TUM_media_number | 040004814793 |
| DE-BY-UBM_katkey | 2454360 |
| DE-BY-UBM_local_subject | Biostatistik. - Evolutionstheorie |
| DE-BY-UBM_media_number | 41621803610018 |
| _version_ | 1823052110576484352 |
| adam_text | HANS-GEORG BEYER THE THEORY OF EVOLUTION STRATEGIES WITH 52 FIGURES AND
9 TABLES SPRINGER CONTENTS 1. INTRODUCTION 1 1.1 A SHORT
CHARACTERIZATION OF THE EA 1 1.2 THE EVOLUTION STRATEGY 4 1.2.1 THE (N/P
+ A)-ES ALGORITHM 4 1.2.2 THE GENETIC OPERATORS OF THE ES 7 1.2.2.1 THE
SELECTION OPERATOR 8 1.2.2.2 THE MUTATION OPERATOR 9 1.2.2.3 THE
REPRODUCTION OPERATOR 11 1.2.2.4 THE RECOMBINATION OPERATOR 12 1.3 THE
CONVERGENCE OF THE EVOLUTION STRATEGY 14 1.3.1 ES CONVERGENCE - GLOBAL
ASPECTS 15 1.3.2 ES CONVERGENCE - LOCAL ASPECTS 17 1.4 BASIC PRINCIPLES
OF EVOLUTIONARY ALGORITHMS 18 1.4.1 EVOLVABILITY 18 1.4.2 EPP, GR, AND
MISR 20 1.4.2.1 EPP - THE EVOLUTIONARY PROGRESS PRINCIPLE... 20 1.4.2.2
GR - THE GENETIC REPAIR HYPOTHESIS 21 1.4.2.3 THE MISR PRINCIPLE 21 1.5
THE ANALYSIS OF THE ES - AN OVERVIEW 22 2. CONCEPTS FOR THE ANALYSIS OF
THE ES 25 2.1 LOCAL PROGRESS MEASURES 25 2.1.1 THE QUALITY GAIN Q 26
2.1.2 THE PROGRESS RATE IP 28 2.1.3 THE NORMAL PROGRESS IP R 30 2.2
MODELS OF FITNESS LANDSCAPES 31 2.2.1 THE (HYPER-)SPHERE MODEL 32 2.2.2
THE HYPERPLANE 33 2.2.3 CORRIDOR AND DISCUS - HYPERPLANES WITH
RESTRICTIONS . 34 2.2.4 QUADRATIC FUNCTIONS AND LANDSCAPES OF
HIGHER-ORDER . 35 2.2.5 THE BIT COUNTING FUNCTION ONEMAX 36 2.2.6 NOISY
FITNESS LANDSCAPES 36 2.3 THE DIFFERENTIAL-GEOMETRICAL MODEL FOR
NON-SPHERICAL FITNESS LANDSCAPES 37 XIV CONTENTS 2.3.1 FUNDAMENTALS OF
THE DIFFERENTIAL-GEOMETRICAL MODEL .. 38 2.3.1.1 THE LOCAL HYPERPLANE DQ
Y 38 2.3.1.2 THE METRIC TENSOR G A/3 39 2.3.1.3 THE SECOND FUNDAMENTAL
FORM 40 2.3.1.4 THE MEAN CURVATURE (X) 41 2.3.2 THE CALCULATION OF THE
MEAN RADIUS R { C) 43 2.3.2.1 THE METRIC TENSOR 43 2.3.2.2 THE 6 Q/3
-TENSOR 44 2.3.2.3 THE COMPUTATION OF THE MEAN RADIUS R^) * * 45 2.4 THE
ES DYNAMICS 47 2.4.1 THE I2-DYNAMICS 48 2.4.2 THE SPECIAL CASE A*{G) =
CONST 49 3. THE PROGRESS RATE OF THE (1 + A)-ES ON THE SPHERE MODEL 51
3.1 THE EXACT (1 + 1)-ES THEORY 51 3.1.1 THE PROGRESS RATE WITHOUT NOISE
IN FITNESS MEASUREMENTS 54 3.1.2 THE PROGRESS RATE AT DISTURBED FITNESS
MEASUREMENTS 57 3.2 ASYMPTOTIC FORMULAE FOR THE (1 + A)-ES 61 3.2.1 A
GEOMETRICAL ANALYSIS OF THE (1 + 1)-ES 61 3.2.1.1 THE ASYMPTOTE OF THE
MUTATION VECTOR Z ... 62 3.2.1.2 THE PROGRESS RATE OF THE (1 + 1)-ES ON
THE SPHERE MODEL 64 3.2.1.3 THE SUCCESS PROBABILITY P S I +1 AND THE EPP
. 68 3.2.2 THE ASYMPTOTIC +X INTEGRAL 69 3.2.3 THE ANALYSIS OF THE (L,
A)-ES 71 3.2.3.1 THE PROGRESS RATE 1A 71 3.2.3.2 THE PROGRESS
COEFFICIENT C HX 74 3.2.4 THE ANALYSIS OF THE (1 + A)-ES 77 3.2.4.1
THE PROGRESS RATE 77 3.2.4.2 THE SUCCESS PROBABILITY P SL+A 79 3.2.4.3
THE PROGRESS FUNCTION D^(X) 79 3.3 THE ASYMPTOTIC ANALYSIS OF THE (1 +
A)-ES 80 3.3.1 THE THEORY OF THE (1 + A) PROGRESS RATE 80 3.3.1.1
PROGRESS INTEGRALS AND ACCEPTANCE PROBABILITIES 80 3.3.1.2 THE
ASYMPTOTIC FITNESS MODEL AND THE P(Q X X) DENSITY 83 3.3.1.3 THE
CALCULATION OF PI (Q) 85 3.3.2 ON THE ANALYSIS OF THE (1, A)-ES 86
3.3.2.1 THE ASYMPTOTIC YT - FORMULA 86 3.3.2.2 THE DYNAMICS OF THE (1,
A)-ES 89 3.3.3 ON THE ANALYSIS OF THE (1 + A)-ES 93 CONTENTS XV 3.3.3.1
THE ASYMPTOTIC Y ? + - INTEGRAL AND P S - 1+X 93 3.3.3.2 AN (ALMOST)
NECESSARY EVOLUTION CRITERION FOR (1 + A)-ES 95 3.3.3.3 SOME ASPECTS OF
THE (1 + 1)-ES 97 3.3.4 CONVERGENCE IMPROVEMENT BY INHERITING SCALED
MUTATIONS 102 3.3.4.1 THEORETICAL FUNDAMENTALS 102 3.3.4.2 DISCUSSION OF
THE (1, A)-ES 103 3.4 THE IV-DEPENDENT (1, A) PROGRESS RATE FORMULA 104
3.4.1 MOTIVATION 104 3.4.2 THE P(R) DENSITY 105 3.4.3 THE DERIVATION OF
THE IP* PROGRESS RATE FORMULA 107 3.4.4 COMPARISON WITH EXPERIMENTS 109
3.4.5 A NORMAL APPROXIMATION FOR P(R) ILL 4. THE (1 + A) QUALITY GAIN
113 4.1 THE THEORY OF THE (1 + A) QUALITY GAIN 113 4.1.1 THE Q LTA
INTEGRAL 113 4.1.2 ON THE APPROXIMATION OF P Z (Z) 115 4.1.3 ON
APPROXIMATING THE QUANTILE FUNCTION P^ 1 (F) .... 118 4.1.4 THE ~Q X X
FORMULA . 119 4.1.5 THE Q 1+X FORMULA 120 4.2 FITNESS MODELS AND
MUTATION OPERATORS 122 4.2.1 THE GENERAL QUADRATIC MODEL AND CORRELATED
MUTATIONS 122 4.2.2 THE SPECIAL CASE OF ISOTROPIC GAUSSIAN MUTATIONS .
.. 125 4.2.3 EXAMPLES OF NON-QUADRATIC FITNESS FUNCTIONS 126 4.2.3.1
BIQUADRATIC FITNESS WITH ISOTROPIC GAUSSIAN MUTATIONS 126 4.2.3.2 THE
COUNTING ONES FUNCTION ONEMAX 127 4.3 EXPERIMENTS AND INTERPRETATIONS OF
THE RESULTS 131 4.3.1 NORMALIZATION 131 4.3.1.1 QUADRATIC FITNESS,
ISOTROPIC GAUSSIAN MUTA- TIONS AND THE DIFFERENTIAL-GEOMETRIC MODEL. . .
131 4.3.1.2 THE NORMALIZATION FOR THE BIQUADRATIC CASE . 134 4.3.2
EXPERIMENTS AND APPROXIMATION QUALITY 135 4.3.3 QUALITY GAIN OR PROGRESS
RATE? 137 5. THE ANALYSIS OF THE (/X, A)-ES 143 5.1 FUNDAMENTALS AND
THEORETICAL FRAMEWORK 143 5.1.1 PRELIMINARIES 143 5.1.2 THE (/I, A)
ALGORITHM AND THE /J M ,A DEFINITION 144 5.1.3 THE Y^X INTEGRAL 146 XVI
CONTENTS 5.1.4 FORMAL APPROXIMATION OF THE OFFSPRING DISTRIBUTION P{R)
147 5.1.5 ESTIMATION OF R, S, AND 7, AND OF FJR , MO N , AND M 3LRM _.
7. ... .. . 150 5.1.6 THE SIMPLIFICATION OF R R M , M- 2 R M , AND M^ R
M 153 5.1.7 THE STATISTICAL APPROXIMATION OF R, S, AND 7 156 5.1.8 THE
INTEGRAL EXPRESSION OF ((AR) 2 ) 159 5.1.9 THE INTEGRAL EXPRESSION OF
((AR) 3 ) 162 5.1.10 APPROXIMATION OF THE STATIONARY STATE - THE
SELF-CONSISTENT METHOD 166 5.2 ON THE ANALYSIS IN THE LINEAR 7
APPROXIMATION 168 5.2.1 THE LINEAR 7 APPROXIMATION 168 5.2.2 THE
APPROXIMATION OF THE TP^^X INTEGRAL 169 5.2.3 THE APPROXIMATION OF S (S
+1 ) 172 5.2.3.1 THE I A INTEGRAL 173 5.2.3.2 THE I B INTEGRAL 175
5.2.3.3 COMPOSING THE S FL+1 FORMULA 176 5.2.4 THE APPROXIMATION OF
7^ +1 ) 176 5.2.4.1 THE I C INTEGRAL 177 5.2.4.2 THE I D INTEGRAL 178
5.2.4.3 THE I E INTEGRAL 181 5.2.4.4 COMPOSING THE -YIS+I) FORMULA 182
5.2.5 THE SELF-CONSISTENT METHOD AND THE TP* X FORMULAE . . . 183 5.3
THE DISCUSSION OF THE {P., A)-ES . 185 5.3.1 THE COMPARISON WITH
EXPERIMENTS 185 5.3.1.1 DATA EXTRACTION FROM ES RUNS 185 5.3.1.2 THE ES
SIMULATIONS FOR A = CONST AND A* = CONST 186 5.3.2 SIMPLIFIED * A
FORMULAE AND THE PROGRESS COEFFICIENT C MIA 188 5.3.2.1 THE DERIVATION
OF THE IP*^ X FORMULAE 188 5.3.2.2 EPP, THE PROPERTIES OF C ^X, AND THE
FITNESS EFFICIENCY 189 5.3.3 THE {P., A)-ES ON THE HYPERPLANE 192 5.3.4
THE EXPLORATION BEHAVIOR OF THE (P, A)-ES 194 5.3.4.1 EVOLUTION IN THE
(R,7;) PICTURE 194 5.3.4.2 THE RANDOM WALK IN THE ANGULAR SPACE .... 195
5.3.4.3 EXPERIMENTAL VERIFICATION AND DISCUSSION .... 199 5.3.4.4 FINAL
REMARKS ON THE SEARCH BEHAVIOR OF THE (/X,A)-ES 199 6. THE (/J,/N, A)
STRATEGIES - OR WHY SEX MAY BE GOOD ... 203 6.1 THE INTERMEDIATE
(P,/P,, A)-ES 203 6.1.1 FOUNDATIONS OF THE (P,/P, A ) THEORY 204 6.1.1.1
THE (PIP,, ) ALGORITHM 204 CONTENTS XVII 6.1.1.2 THE DEFINITION OF THE
PROGRESS RATE IP^/^X * * * 205 6.1.1.3 THE STATISTICAL APPROXIMATION OF
^ M /^,A 206 6.1.2 THE CALCULATION OF WMJ.A 210 6.1.2.1 THE DERIVATION
OF THE EXPECTED VALUE 7^ 210 6.1.2.2 THE DERIVATION OF THE EXPECTED
VALUE (H 2 )... 213 6.1.2.3 THE (P/P,, ) PROGRESS RATE 215 6.1.3 THE
DISCUSSION OF THE (P/P,,X) THEORY 216 6.1.3.1 THE COMPARISON WITH
EXPERIMENTS AND THE CASE N - * OO 216 6.1.3.2 ON THE BENEFIT OF
RECOMBINATION OR WHY SEX MAY BE GOOD 218 6.1.3.3 SYSTEM CONDITIONS OF
RECOMBINATION 222 6.1.3.4 THE (P/P,, )-ES AND THE OPTIMAL P CHOICE . .
224 6.1.3.5 THE EXPLORATION BEHAVIOR OF THE (P/P,, A)-ES 229 6.2 THE
DOMINANT (P/P D , X)-ES 232 6.2.1 A FIRST APPROACH TO THE ANALYSIS OF
THE (P/P D , X)-ES . 232 6.2.1.1 THE (P/P D , )-ES ALGORITHM AND THE
DEFINITION OF IP LI / TTDT X 232 6.2.1.2 A SIMPLE MODEL FOR THE ANALYSIS
OF THE (P./P D ,X)-ES 233 6.2.1.3 THE ISOTROPIC SURROGATE MUTATIONS 235
6.2.1.4 THE PROGRESS RATE F* FL/FIDA 237 6.2.2 THE DISCUSSION OF THE
(P/P D , A)-ES 239 6.2.2.1 THE COMPARISON WITH EXPERIMENTS AND THE CASE
N - OO 239 6.2.2.2 THE MISR PRINCIPLE, THE GENETIC DRIFT, AND THE GR
HYPOTHESIS 240 6.3 THE ASYMPTOTIC PROPERTIES OF THE (P/P, A)-ES 246
6.3.1 THE C M/MJA COEFFICIENT 247 6.3.1.1 THE ASYMPTOTIC EXPANSION OF
THE C N/N, COEFFICIENT 247 6.3.1.2 THE ASYMPTOTIC ORDER OF THE C N/N,
COEFFICIENTS 250 6.3.2 THE ASYMPTOTIC PROGRESS LAW 250 6.3.3 FITNESS
EFFICIENCY AND THE OPTIMAL I? CHOICE 252 6.3.3.1 ASYMPTOTIC FITNESS
EFFICIENCY T? M / M] A F THE (P/P, )-ES 252 6.3.3.2 THE RELATION TO
THE (1 + 1)-ES 252 6.3.4 THE DYNAMICS AND THE TIME COMPLEXITY OF THE
(P/P,, A)-ES 255 7. THE (1, A)-O--SELF-ADAPTATION 257 7.1 INTRODUCTION
257 7.1.1 CONCEPTS OF CR-CONTROL 257 XVIII CONTENTS 7.1.2 THE
^-SELF-ADAPTATION 259 7.1.3 THE (1, A)-CTSA ALGORITHM 261 7.1.4
OPERATORS FOR THE MUTATION OF THE MUTATION STRENGTH . 261 7.2
THEORETICAL FRAMEWORK FOR THE ANALYSIS OF THE CRSA 263 7.2.1 THE
EVOLUTIONARY DYNAMICS OF THE (1, A)-CRSA-ES 264 7.2.1.1 THE R EVOLUTION
265 7.2.1.2 THE , EVOLUTION 266 7.2.2 THE MICROSCOPIC ASPECTS 268
7.2.2.1 THE DENSITY P 1; I(R) OF A SINGLE DESCENDANT... 269 7.2.2.2 THE
TRANSITION DENSITY PI-X(R) 270 7.2.2.3 THE TRANSITION DENSITY PI ; A(C)
271 7.2.2.4 THE V?W AND ^ (FC) -SAR FUNCTIONS 272 7.3 DETERMINATION OF
THE PROGRESS RATE AND THE SAR 275 7.3.1 PROGRESS INTEGRALS (K) 275
7.3.1.1 NUMERICAL EXAMPLES FOR THE PROGRESS RATE IP* 275 7.3.1.2 AN
ANALYTIC IF* FORMULA FOR P A = P 11 , X = 2 . . 276 7.3.1.3 THE R - 0
AND (3 - * 0 APPROXIMATION FOR D* . 279 7.3.2 THE SAR FUNCTIONS / (FC
280 7.3.2.1 NUMERICAL EXAMPLES FOR T/^ 1 , DISCUSSION, AND COMPARISON
WITH EXPERIMENTS 280 7.3.2.2 AN ANALYTIC IP FORMULA FOR P A = P U , X =
2. . . 283 7.3.2.3 BOUNDS FOR V 286 7.3.2.4 ANALYTIC APPROXIMATION OF
4 ^ FOR SMALL ^* AND R - GENERAL ASPECTS 289 7.3.2.5 APPROXIMATIONS FOR
IP, T/ ( 2 AND D^ 294 7.4 THE (1, A)-CTSA EVOLUTION (I) - DYNAMICS IN
THE DETERMINISTIC APPROXIMATION 299 7.4.1 THE EVOLUTION EQUATIONS OF THE
(1, A)-ASA-ES 299 7.4.2 THE ES IN THE STATIONARY STATE 300 7.4.2.1
DETERMINING THE STATIONARY STATE 300 7.4.2.2 OPTIMAL ES PERFORMANCE AND
THE L/ /N RULE 302 7.4.2.3 THE DIFFERENTIAL EQUATION OF THE A EVOLUTION,
THE TRANSIENT BEHAVIOR FOR SMALL ^ (0) ^* S , AND THE STATIONARY R
DYNAMICS 303 7.4.2.4 APPROACHING THE STEADY-STATE FROM C* » S . 308
7.5 THE (1, A)-CRSA EVOLUTION (II) - DYNAMICS WITH FLUCTUATIONS . 309
7.5.1 MOTIVATION 309 7.5.2 CHAPMAN-KOLMOGOROV EQUATION AND TRANSITION
DENSITIES 309 7.5.3 MEAN VALUE DYNAMICS OF THE R EVOLUTION 313 7.5.4
MEAN VALUE DYNAMICS OF THE ;* EVOLUTION 315 7.5.5 APPROXIMATE EQUATIONS
FOR THE STATIONARY A^ STATE .. 317 7.5.5.1 THE INTEGRAL EQUATION OF THE
STATIONARY P( CONTENTS XIX 7.5.5.2 AN APPROACH FOR SOLVING THE MOMENTUM
EQUATIONS 319 7.5.6 DISCUSSION OF THE STATIONARY STATE AND THE 1/Y/N
RULE 320 7.5.6.1 COMPARISON WITH ES EXPERIMENTS 320 7.5.6.2 SPECIAL
ANALYTICAL CASES 321 7.5.6.3 THE R-SCALING RULE 323 7.6 FINAL REMARKS ON
THE A SELF-ADAPTATION 324 APPENDICES 327 A. INTEGRALS 329 A.I DEFINITE
INTEGRALS OF THE NORMAL DISTRIBUTION 329 A.2 INDEFINITE INTEGRALS OF THE
NORMAL DISTRIBUTION 331 A.2.1 INTEGRALS OF THE FORM I A ^(X) = F_ = ^ T
3 ER^^DT .... 331 A.2.2 INTEGRALS OF THE FORM I${X) = F_ = ^ T 0 E~^^(T)
DT .... 332 A.3 SOME INTEGRAL IDENTITIES 334 B. APPROXIMATIONS 337 B.I
FREQUENTLY USED TAYLOR EXPANSIONS 337 B.2 THE HERMITE POLYNOMIALS HE FE
(A;) 339 B.3 CUMULANTS, MOMENTS, AND APPROXIMATIONS 341 B.3.1
FUNDAMENTAL RELATIONS 341 B.3.2 THE WEIGHT COEFFICIENTS FOR THE DENSITY
APPROXIMA- TION OF A STANDARDIZED RANDOM VARIABLE 344 B.4 APPROXIMATION
OF THE QUANTILE FUNCTION 349 C. THE NORMAL DISTRIBUTION 351 C.I AF(0,L)
DISTRIBUTION FUNCTION, GAUSSIAN INTEGRAL, AND ERROR FUNCTION 351 C.2
ASYMPTOTIC ORDER OF THE MOMENTS OF ^ 354 C.3 PRODUCT MOMENTS OF
CORRELATED GAUSSIAN MUTATIONS 355 C.3.1 FUNDAMENTAL RELATIONS 355 C.3.2
DERIVATION OF THE PRODUCT MOMENTS 356 D. (1, A)-PROGRESS COEFFICIENTS
359 D.I ASYMPTOTICS OF THE PROGRESS COEFFICIENTS D X 359 D.I.I AN
ASYMPTOTIC EXPANSION FOR THE D X COEFFICIENTS.. . . 359 D.I.2 THE
ASYMPTOTIC C HX AND D[ 2 { FORMULAE 360 D.I.3 AN ALTERNATIVE DERIVATION
FOR C X 361 D.2 TABLE OF PROGRESS COEFFICIENTS OF THE (1, A)-ES 363
REFERENCES 365 INDEX 37 3
|
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| discipline | Biologie Informatik |
| format | Book |
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| id | DE-604.BV013652747 |
| illustrated | Illustrated |
| indexdate | 2025-02-03T16:44:36Z |
| institution | BVB |
| isbn | 3540672974 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009328407 |
| oclc_num | 247928112 |
| open_access_boolean | |
| owner | DE-703 DE-29T DE-91 DE-BY-TUM DE-824 DE-19 DE-BY-UBM DE-M347 DE-634 DE-11 DE-525 DE-20 |
| owner_facet | DE-703 DE-29T DE-91 DE-BY-TUM DE-824 DE-19 DE-BY-UBM DE-M347 DE-634 DE-11 DE-525 DE-20 |
| physical | XIX, 380 S. graph. Darst. |
| publishDate | 2001 |
| publishDateSearch | 2001 |
| publishDateSort | 2001 |
| publisher | Springer |
| record_format | marc |
| series2 | Natural computing series |
| spellingShingle | Beyer, Hans-Georg The theory of evolution strategies with 9 tables Evolutionsstrategie Computer algorithms Evolutionary programming (Computer science) Evolutionsstrategie (DE-588)4015930-9 gnd |
| subject_GND | (DE-588)4015930-9 |
| title | The theory of evolution strategies with 9 tables |
| title_auth | The theory of evolution strategies with 9 tables |
| title_exact_search | The theory of evolution strategies with 9 tables |
| title_full | The theory of evolution strategies with 9 tables Hans-Georg Beyer |
| title_fullStr | The theory of evolution strategies with 9 tables Hans-Georg Beyer |
| title_full_unstemmed | The theory of evolution strategies with 9 tables Hans-Georg Beyer |
| title_short | The theory of evolution strategies |
| title_sort | the theory of evolution strategies with 9 tables |
| title_sub | with 9 tables |
| topic | Evolutionsstrategie Computer algorithms Evolutionary programming (Computer science) Evolutionsstrategie (DE-588)4015930-9 gnd |
| topic_facet | Evolutionsstrategie Computer algorithms Evolutionary programming (Computer science) |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009328407&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT beyerhansgeorg thetheoryofevolutionstrategieswith9tables |