Hi there !

I am doing research on Nested Monte Carlo algorithm which is a Monte Carlo playout method improved by nesting the evaluation function inside another evaluation function; secondly, by measuring and utilising the depth of the playout; and thirdly, by incorporating pruning strategies that eliminate unnecessary searches and avoid traps.

I know the algorithm designer tried it on games such as sudoku 16*16, Morpion Solitaire or SameGame. I would love to apply it to a real life problem to cut my teeth of researcher apprentice. Do you have any idea ?

@Marine1 hi, welcome, interesting, some of the cutting edge research in this area is now on Go and video games by Deepmind. but maybe you want something simpler. but think these are not out of reach for a talented researcher. recently have some related ideas myself am wanting to pursue... vzn1.wordpress.com/2018/01/04/…

Someone told me about a cool algorithm book: books.goalkicker.com/AlgorithmsBook compiled from a StackOverflow data dump(?) Has quick handy references to most popular algorithms and implementations for a lot of them.

@ryan Interesting stuff, although I prefer my 'lower bound' (cpbook.net ) as a reference.

although, page 14. The artifacts. THEY HURT.

Huh, didn't expect to see Dynamic Time Warping there. I'm aware of many data-analysis applications (mostly in geographical data, where I'm currently working on), but it's interesting to see that this is relevant for some day-to-day programmers.