Hello list,
I recently defended my PhD. Maybe it's of interest to some of you who
are applying MCTS to one-player or adversarial two-player domains.
You can download a revised edition (basically fewer typos than the
printed thing) here:
http://hendrikbaier.jimdo.com/research/
Cheers,
Hendrik
I like the topic of aesthetics in gameplay. I think the focus in
previous studies in chess was more on compositions (artificial
problems) than on actual games, so the question is not whether a
player plays beautifully, but whether a problem is elegant and
beautiful. And they did come up with
Hi Xavier,
I have considered this, but even level-2 Nested MCTS requires quite a
bit of thinking time. Let's say you can do 1000 playouts per second in
your game, and you want to do at least 500 playouts on levels 1 and 2
for each move decision. Assume your playouts have 50 moves on average.
Then
Hi,
you might want to have a look at our paper on time management for MCTS:
https://dke.maastrichtuniversity.nl/m.winands/documents/time_management_for_monte_carlo_tree_search.pdf
We used Go in the beginning and then also generalized to some other
games; the most successful strategy was quite a
, a pleasure to read.
Hendrik Baier
> So there is a superstrong neural net.
>
> 1) Where is the semantic translation of the neural net to human theory
> knowledge?
>
> 2) Where is the analysis of the neural net's errors in decision-making?
>
> 3) Where is the world-wi
