artificial intelligence - What to Do when Monte Carlo Tree Search Hits Memory Limit -


i have taken interest monte carlo tree search applied in games recently.

i have read several papers, use "monte-carlo tree search" phd thesis chaslot, g find more easy understand basics of monte carlo tree search

i have tried code it, , stuck on problem. algorithm tries expand 1 node game tree every 1 simulation. escalates memory problem. have read paper, doesnt seem explain technique if hits memory limit.

can suggest should technique if hits memory limit?

you can see paper here : http://www.unimaas.nl/games/files/phd/chaslot_thesis.pdf

you can throw away nodes number of visits smaller threshold not visited (how many playouts ago). that's quick not efficient solution. it's better implement progressive widening too.


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