Somewhere in space flying ASI in the form of a cloud with nanobots that continuously simulates the future. He does this for to know all of the risks and opportunities of the event in advance. So, he is able to conduct more effective research, for example to avoid loss of a time. Of course, if the future of modeling uses less resources than saved. There is only one problem—its sensors indicate that at a distance of thousands parsecs no other ASI. But there is a probability (0,0...1%) that another ASI will suddenly appear next to us using the teleport about which the first intellect is nothing known. The calculation shows that the probability of 0.0...1% appearance and 5% that other ASI will destroy the first algorithm. That will selects the first algorithm? Waste of resources to solve the problem with low probability or the probability the destruction.
On the whole the algorithm is able to create a a lot of markers, which he will have to check in real world. And these markers will be correct probabilistic models all the time.
So, you can build a model in which the highest probability density is verified most densely markers on the basis of genetic algorithms.
Theoretical example.
Somewhere in space flying ASI in the form of a cloud with nanobots that continuously simulates the future. He does this for to know all of the risks and opportunities of the event in advance. So, he is able to conduct more effective research, for example to avoid loss of a time. Of course, if the future of modeling uses less resources than saved. There is only one problem—its sensors indicate that at a distance of thousands parsecs no other ASI. But there is a probability (0,0...1%) that another ASI will suddenly appear next to us using the teleport about which the first intellect is nothing known. The calculation shows that the probability of 0.0...1% appearance and 5% that other ASI will destroy the first algorithm. That will selects the first algorithm? Waste of resources to solve the problem with low probability or the probability the destruction.
On the whole the algorithm is able to create a a lot of markers, which he will have to check in real world. And these markers will be correct probabilistic models all the time.
So, you can build a model in which the highest probability density is verified most densely markers on the basis of genetic algorithms.