You mentioned at the end that as humanity does things that require a more complex simulation, such as exploring the rest of our solar system, the change of us being in a simple simulation (and therefore a simulation) reduce. How do you think this changes when you take into concideration the probabilities of us reaching those goals? A concrete example; our simulators might be running ancestor simulations to figure out “what is the probability of us discovering faster than light travel”. To answer this they create 10^6 simple simulations of earth, with varying starting conditions. To answer their question they only need to simulate the solar system in significant resolution for those simulations who have explored it, which may be an slim slice of the overall set of simulations. In this example, a simulation who has explored the solar system cannot say “my simulation is computationally expensive to run, therefore there’s a low chance of it being simulated” because the simulators can upgrade simple simulations to complex ones once they have reached sufficient complexity.
Have I got a point here? Many thanks for yours (or any onlookers) thoughts on the matter!
Appologies for the verbose phrasing of the question; “If you cannot explain it simply, you do not know it well enough” and I certainly don’t know it well enough. :)
Those extended simulations are more complex than non extended simulations. The simplicity assumptions tells you that those extended simulations are less likely, and the distribution is dominated by non extended simulations (assuming that they are considerably less complex).
To see this more clearly, take the point of view of the simulators, and for simplicity neglect all the simulations that are running t=now. So, consider all the simulations ever run by the simulators so far and that have finished. A simulation is considered finished when it is not run anymore. If a simulation of cost C1 is “extended” to 2 C1, then de facto we call it a C2 simulation. So, there is well defined distributions of finished simulations C1, C2 (including pure C2 and C1 extended sims), C3 (including pure C3, extended C2, very extended C1, and all the combinations), etc.
You can also include simulations running t=now in the distribution, even though you cannot be sure how to classify them until the finish. Anyway, for large t the number of simulations running now will be a small number w.r.t the number of simulations ever run.
Nitpick: A simulation is never really finished, as it can be reactivated at any time.
You mentioned at the end that as humanity does things that require a more complex simulation, such as exploring the rest of our solar system, the change of us being in a simple simulation (and therefore a simulation) reduce. How do you think this changes when you take into concideration the probabilities of us reaching those goals? A concrete example; our simulators might be running ancestor simulations to figure out “what is the probability of us discovering faster than light travel”. To answer this they create 10^6 simple simulations of earth, with varying starting conditions. To answer their question they only need to simulate the solar system in significant resolution for those simulations who have explored it, which may be an slim slice of the overall set of simulations. In this example, a simulation who has explored the solar system cannot say “my simulation is computationally expensive to run, therefore there’s a low chance of it being simulated” because the simulators can upgrade simple simulations to complex ones once they have reached sufficient complexity.
Have I got a point here? Many thanks for yours (or any onlookers) thoughts on the matter!
Appologies for the verbose phrasing of the question; “If you cannot explain it simply, you do not know it well enough” and I certainly don’t know it well enough. :)
Those extended simulations are more complex than non extended simulations. The simplicity assumptions tells you that those extended simulations are less likely, and the distribution is dominated by non extended simulations (assuming that they are considerably less complex).
To see this more clearly, take the point of view of the simulators, and for simplicity neglect all the simulations that are running t=now. So, consider all the simulations ever run by the simulators so far and that have finished. A simulation is considered finished when it is not run anymore. If a simulation of cost C1 is “extended” to 2 C1, then de facto we call it a C2 simulation. So, there is well defined distributions of finished simulations C1, C2 (including pure C2 and C1 extended sims), C3 (including pure C3, extended C2, very extended C1, and all the combinations), etc.
You can also include simulations running t=now in the distribution, even though you cannot be sure how to classify them until the finish. Anyway, for large t the number of simulations running now will be a small number w.r.t the number of simulations ever run.
Nitpick: A simulation is never really finished, as it can be reactivated at any time.