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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20211208T164413Z
LOCATION:Level 2 - Lobby
DTSTART;TZID=America/Los_Angeles:20211208T180000
DTEND;TZID=America/Los_Angeles:20211208T190000
UID:dac_DAC 2021_sess243_WIP161@linklings.com
SUMMARY:SpecMCTS: Accelerating Monte Carlo Tree Search using Speculative T
 ree Traversal
DESCRIPTION:Networking Reception, Work-in-Progress Poster\n\nSpecMCTS: Acc
 elerating Monte Carlo Tree Search using Speculative Tree Traversal\n\nKim\
 n\nMonte Carlo Tree Search (MCTS) algorithms show great success in decisio
 n-making problems. MCTS requires significant computing loads to make a goo
 d decision. Parallelizing MCTS is challenging because MCTS is a sequential
  process. We present SpecMCTS, which accelerates MCTS by speculatively tra
 versing the search tree. SpecMCTS uses a pair of DNN models, the speculati
 on model and the main model.  The faster (but less accurate) speculation m
 odel accelerates the tree search while the more accurate main model improv
 es the decision quality. SpecMCTS accelerates MCTS for the game of Go by u
 p to 3.81x while having better decision quality than previous approaches.\
 n\nVirtual Program: Presented In-Person
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