Here's a thought: apply successive A/B testing in steps similarly to the Metropolis-Hastings algorithm. The core sys that for each new test (each new "jump") yo

Here's a thought: apply successive A/B testing in steps similarly to the Metropolis-Hastings algorithm. The core sys that for each new test (each new "jump") you evaluate the probability ratio a = p_new/p_old where p_x is the probability that x is successful. If a is greater than 1, go with the new, if it's less than 1, still go with the new a% of the time. By implementing parts of this algorithm you might be able to generate a random walk scenario that is local minima resistant.