Randomized Hill Climbing improvement

[wtld]

According to referenced "Clever Algorithms: Nature-Inspired Programming Recipes":

neighbors with better or equal cost should be accepted, allowing the technique to navigate across plateaus in the response surface

I suggest a change in the code like this:

while (attempts < max_attempts) and (iters < max_iters):
    iters += 1
    attempts += 1

    # Find random neighbor and evaluate fitness
    next_state = problem.random_neighbor()
    next_fitness = problem.eval_fitness(next_state)

    improvement = next_fitness - problem.get_fitness()

    # If the neighbor is better or equal move to that state
    if improvement >= 0:
        problem.set_state(next_state)
        # if better than reset attempts counter
        if improvement > 0: 
            attempts = 0

I personally work with problems where this small change has a big impact on results.

[walintonc]

Thanks, @wtld
Can you create Pull Request with your proposed changes so that it can be properly reviewed?