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`@@ -116,11 +116,13 @@ DA.solve(plot=True)`
`116`	`116`	`From the console we can deduce the optimal result (see Fig. 4) . The global optimal has a fitness of 25, while duelist algorithm found 25.01. Error of 0.01 can be reduced by putting more maximum generations in solver.`
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`118`	`118`	`![result1](images/results.PNG)`
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`119`	`120`	`Fig 4. Optimal Results in Console`
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`121`	`122`	`We can see that the algorithm quickly converges to the optimal point (see Fig. 5) as reported by the original article.`
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`123`	`124`	`![result2](images/results2.png)`
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`124`	`126`	`Fig 5. Quick convergence of Duelist Algorithm`
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`126`	`128`	`For more examples refer to the python scripts in "examples" folder. [https://github.com/tsyet12/Duelist-Algorithm-Python/tree/master/examples]`

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