### Table 1: Various Mutation Probability Results Mutation

"... In PAGE 6: ... We fixed number of generation to 600 to limit the execution time, mark the last detected vector to the test sequence length, and run five times per circuits. The experiment results in Table1 are average of five runs, and a new random seed for GA was used for each run. The effects of mutation probability on fault coverage were also investigated.... In PAGE 6: ... The effects of mutation probability on fault coverage were also investigated. Results are shown in Table1 averaged over five runs for various mutation tares used during test generation. Tournament selection without replacement and uniform crossover was used.... ..."

### Table 4. Effect of the specification of the mutation probability.

"... In PAGE 15: ... The other parameter values were specified in the same manner as in the previous computer simulations. Simulation results are summarized in Table4 . Table 4 shows the average payoff obtained from ten independent trials for each combination of m P and N .... In PAGE 15: ...est result was obtained in the case of no mutation (i.e., = m P 0) when the size of the neighborhood structure was specified as = N 4. We can also observe the positive effect of the mutation operation in Table4 . That is, the average payoff was improved by increasing the mutation probability from 0 to 0.... ..."

### Table 1 Range of mutation probabilities on edges

"... In PAGE 31: ... Then, with probability tending to 1, diam(T)= log n will lie between c and 2c. In Table1 , we summarize sequence length that su ce for accurate reconstruction with high probability of WAM and DCM, and compare these to the sequence lengths that su ce for the Agarwala et al. algorithm, according to the analyses that we have given above (thus, our summary is based upon (12), (37), and Theorems 10 and 13).... ..."

### Table 3. Crossover and mutation probability used in the GA.

2002

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### Table 7: Results for different mutation probabilities.

### Table 1: Mutation and crossover probabilities

"... In PAGE 7: ... We used one-point crossover. The runs of the genetic algorithm were analyzed by three values in Table1 . These parameters are (from left to right): 1.... In PAGE 7: ... This limit was determined specially so that the CD differences (it has the biggest weight) can be regarded zero. Table1 illustrates several experiments of different (D4D1D9D8, D4CRD6D3D7D7) pairs in the one dimensional continuous case. The runs with each settings of the pair were repeated seven times, the table consists the averages of the seven exper- iments.... In PAGE 7: ... Note that each element of the line D4D1D9D8 BP BCBN BD is very good, but the alteration of indi- viduals from generation to generation are too big, thus the relation between the parents and the offsprings is loose. Table1 illustrates that 150 for the maximum number of generations is enough (with 31 population-size) in the con- tinuous cases. But in the discrete cases it required greater maximal age because of the greater number of optimization parameters.... ..."

### Table 1: Mutation and crossover probabilities

"... In PAGE 7: ... We used one-point crossover. The runs of the genetic algorithm were analyzed by three values in Table1 . These parameters are (from left to right): 1.... In PAGE 7: ... This limit was determined specially so that the CD differences (it has the biggest weight) can be regarded zero. Table1 illustrates several experiments of different (D4 D1D9D8 , D4 CRD6D3D7D7 ) pairs in the one dimensional continuous case. The runs with each settings of the pair were repeated seven times, the table consists the averages of the seven exper- iments.... In PAGE 7: ... Note that each element of the line D4 D1D9D8 BP BCBN BD is very good, but the alteration of indi- viduals from generation to generation are too big, thus the relation between the parents and the offsprings is loose. Table1 illustrates that 150 for the maximum number of generations is enough (with 31 population-size) in the con- tinuous cases. But in the discrete cases it required greater maximal age because of the greater number of optimization parameters.... ..."

### Table 6. Percentage of mutual cooperation for each specification of the mutation probability

2005

"... In PAGE 23: ...-22- mutual cooperation for various specifications of the crossover and mutation probabilities in Table 5 and Table6 where high percentages of mutual cooperation (over 70%) are highlighted by boldface. Table 5 shows the effect of the crossover probability on the percentage of mutual cooperation.... In PAGE 23: ... High percentages of mutual cooperation were obtained in Table 5 even in the case of the crossover probability being zero. On the other hand, Table6 shows the effect of the mutation probability on the percentage of mutual cooperation. High percentages of mutual cooperation were obtained in Table 6 in a wide range of mutation probabilities while a too large mutation probability decreased the percentage of mutual cooperation.... In PAGE 23: ... On the other hand, Table 6 shows the effect of the mutation probability on the percentage of mutual cooperation. High percentages of mutual cooperation were obtained in Table6 in a wide range of mutation probabilities while a too large mutation probability decreased the percentage of mutual cooperation. Table 5.... In PAGE 23: ... Since these results are similar to Fig. 13, they are omitted in Table 5 and Table6 . These tables show that the combination of the smallest interaction neighborhood ) ( IPD i N and a small mating neighborhood ) ( GA i N... ..."

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### Table 3: Crossover and mutation probability used in stan- dard GA.

2001

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