Merge branch 'first-rough-plan' into 'master'

add some remarks made in the first discussion

See merge request !1

plan.md

+# Adaptive
+
+We propose to use local criteriums for sampling combined with global updates.
+This defines a family of straightforwardly parallelizable algorithms which are useful for intermediary cost simulations.
+
+When your function evaluation is very expensive, full-scale Bayesian sampling will perform better, however, there is a broad class of simulations that are in the right regime for Adaptive to be beneficial.
+
+We can include things like:
+* Asymptotically complexity of algorithms
+* Setting of the problem, which classes of problems can be handled with Adaptive
+* Loss-functions examples (maybe include [Adaptive quantum dots](https://chat.quantumtinkerer.tudelft.nl/chat/channels/adaptive-quantum-dots))
+* Trials, statistics (such as measuring timings)
+* Line simplification algorithm as a general criterium
+* Desirable properties of loss-functions
+* List potential applications