To construct a map, there must be an expectation of the environment. The CAP theorem lays out an abstract view of how agents can interact in an environment. The common utilization of a semantic interpretation of a response is what enables a map to be built. As an example, if the expectation of a response is that the responding entity must respond if it is non-failing, then a map can be built whereby the atomic expansion of the map happens all at once or not at all. Similarly, if the expectation of a response is that the responding entity may never reply at all, then a map can be built whereby the shrinking of the map happens partially all the time. In a sense, the semantic interpretation that is used to construct the map depends on the probability of error. If the probability of error is very low, then it is a reasonable expectation that every entity must respond if it is non-failing. If the probability of error is very high, then it is not a reasonable expectation that every entity mu
In a highly chaotic system, such as a high temperature gas, it is not ideal to use an atomic causal model. Instead, the effective causal model is to approximate to what extent each atom is interacting with every other atom. If we increase the temperature, then the number of atoms each atom interacts with should increase. As the temperature decreases, the number of atoms each atom interacts with should decrease. If we were to randomly sample any atom, then on average, the atom should interact with a set of atoms of a certain size. Instead of thinking in terms of conditional probabilities and causal implications, we think in terms of sets of interconnected events. And this is because it is not computationally effective to analyze chaotic systems in a linear manner. We can apply the same line of reasoning to sampling. If a system has a particular sampling rate, the inputs to the system are batched according to the sampling rate. In other words, the system cannot discern the ordering of ev