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I would be interested to see whether a genetic algorithm performs better than a hill-climbing one in this context. By hill-climbing I mean searching for a vector in the seven-dimensional space you've defined which makes the biggest improvement in the fitness function. I tend to think hill climbing would converge faster than evolution among random mutations.


Yes, a comparison with hill climbing or with simulated annealing would be nice




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