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Evolutionary Search Knowledge Reservoir Set of possible solutions - PDF document

global maximum local maxima local maxima Evolutionary Search Knowledge Reservoir Set of possible solutions Gleaning a reservoir of knowledge om interactions ith the environment. Selection Fitness dependent number of o


  1. global maximum local maxima local maxima Evolutionary Search • Knowledge Reservoir Set of possible solutions • Gleaning a reservoir of knowledge � om interactions � ith the environment. • Selection Fitness � dependent number of o � spring • The sieve of selection cu � s out incorrect / unuseful � knowledge � . • V ariation V ariations of individual solutions • The learning system invents new variants of its old ideas that are tested against environmental demands.

  2. Individuals : . . . . . . . . . . . . . . . µ Genotype of Phenotype of P opulation of an individual an individual, µ individuals realization Genetic Operators : t 2x x x x . . . . . x . . . . . . . . . . . . . . . x . . . . x x x µ x x x Duplication Mutation Isolation for Recombination t time units Selection and Evaluation : w Q . . . . . . . . . . . . . . . . . . . . . µ µ Q Evaluation Selection Random selection 2x 2x 2x 2x 2x . . . . . . . . . . . . . . . . . . . . . . . . ... Q Q Q 2x 2x 2x . . . . . . . . . . . . . . . . . . . . . . . . . . Q Q ... . . . . Mutation . . . . ... . . 1+ � . . . . . . . . . . . . Q 1 2 � . . Q Q Q . . . . . . . . . . . . . Q Q . . . . . (a) . Selection Evaluation ... (1+ � ) ES . . � . . . . Q 1 2 � . . . (a) (b) (b) (1 , � ) ES (1+1) ES (1,1) ES

  3. 2x 2x 2x 2x 2x 2x w 2x 2x 2x 2x 2x 2x . . . w w . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . µ ... ... Recombination w w w µ µ . . . Mutation . . . . . . Q Q Q Q Q Q ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... Q Q Q � µ+ � . . . Q 1 2 � Q 1 2 � . . . . . . . Selection . . . . . Evaluation . . . ... . . . . . . . . . . . . . . . . . . � Q 1 2 � µ (a) µ (b) . . . . . . . . . µ Object parameters Strategy parameters p : p 1 p 2 p 3 p 4 p 5 s : s 1 s 2 s 3 s 4 s 5 ... ... N 0 + N 0 + MSA, � MSA, � p mut : p' 1 p' 2 p' 3 p' 4 p' 5 s mut : s' 1 s' 2 s' 3 s' 4 s' 5

  4. Object parameters Strategy parameters p : p 1 p 2 p 3 p 4 p 5 s : s 1 s 2 s 3 s 4 s 5 ... ... N 0 + N 0 + MSA, � MSA, � p mut : p' 1 p' 2 p' 3 p' 4 p' 5 s mut : s' 1 s' 2 s' 3 s' 4 s' 5

  5. Object and strategy parameters p 1 s 1 : ( , p 11 ) p 12 p 13 p 14 p 15 s 11 s 12 s 13 s 14 s 15 ( p 2 s 2 , : p 21 ) p 22 p 23 p 24 p 25 s 21 s 22 s 23 s 24 s 25 � . . . � . . . � ( p r s r , : p 11 ) p 22 p 23 p 14 p 25 s 11 s 12 s 23 s 14 s 25 � p1, s1 � = � �� 1 � 4 � 2 � 7 � 9 � 3 � � � p2, s2 � = � �� 3 � 5 � 9 � 8 � 4 � 2 � � � pr, sr � = � �� 1 � 5 � 9 � 7 � 4 � 3 � � Object and strategy parameters p 1 s 1 , : p 11 p 12 p 13 p 14 p 15 s 11 s 12 s 13 s 14 s 15 ( p a s a , : ) p a 1 p a 2 p a 3 p a 4 p a 5 s a 1 s a 2 s a 3 s a 4 s a 5 p 2 s 2 , : p 21 p 22 p 23 p 24 p 25 s 21 s 22 s 23 s 24 s 25 p 1 s 1 , : p 11 p 12 p 13 p 14 p 15 s 11 s 12 s 13 s 14 s 15 � � � p 3 s 3 , : p 31 p 32 p 33 p 34 p 35 s 31 s 32 s 33 s 34 s 35 p 2 s 2 , : p 21 p 22 p 23 p 24 p 25 s 21 s 22 s 23 s 24 s 25 ( p b s b , : p b 1 ) p b 2 p b 3 p b 4 p b 5 s b 1 s b 2 s b 3 s b 4 s b 5 p 4 s 4 , : p 41 p 42 p 43 p 44 p 45 s 41 s 42 s 43 s 44 s 45 p 3 s 3 , : p 31 p 32 p 33 p 34 p 35 s 31 s 32 s 33 s 34 s 35 p 5 s 5 , : p 51 p 52 p 53 p 54 p 55 s 51 s 52 s 53 s 54 s 55 p 4 s 4 , : p 41 p 42 p 43 p 44 p 45 s 41 s 42 s 43 s 44 s 45 � . . . � . . . � p 6 s 6 : , p 61 p 62 p 63 p 64 p 65 s 61 s 62 s 63 s 64 s 65 p 5 s 5 , : p 51 p 52 p 53 p 54 p 55 s 51 s 52 s 53 s 54 s 55 p 7 s 7 , : p 71 s 71 p 6 s 6 : p 72 p 73 p 74 p 75 s 72 s 73 s 74 s 75 , p 61 p 62 p 63 p 64 p 65 s 61 s 62 s 63 s 64 s 65 ( p' s' , : p' 1 ) p' 2 p' 3 p' 4 p' 5 s' 1 s' 2 s' 3 s' 4 s' 5 p 7 s 7 : , p 71 p 72 p 73 p 74 p 75 s 71 s 72 s 73 s 74 s 75 p , : s p , : s p 31 p 62 p 13 p 64 p 15 s 31 s 62 s 33 s 14 s 65 p 31 p 62 p 13 p 64 p 15 s 31 s 62 s 33 s 14 s 65 Gen. 0 Gen. 1 Gen. 2 Gen. 2

  6. Gen. 3 Gen. 4 Gen. 5 Gen. 10 w 2x . . . . . . . . . . . . . . . . . . 2x . . . ... � 0 � 0 µ 1 2x 2x 2x 2x w 2x w 2x . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... µ 0 µ 0 Q Q Q Q Q Q . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... µ 0 + � 0 µ 0 + � 0 Q 1 2 � 0 Q 1 2 � 0 . . . . . . . . . . . . . . . . . . . . . µ 0 µ 0 Q Q . . . . . . . . . . . . . . . . . . . . . 1 � 1 . . . . . . . . . . . . . . . . . . ... � 1 Q . . . . . . . . . . . . . . . . . . ... 1 µ 1

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