Abstract | ||
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Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search heuristic for puzzles and other optimization problems. It achieves state-of-the-art performance on several games including SameGame. In this paper, we design several parallel and distributed NRPA-based search techniques, and we provide a number of experimental insights about their execution. Finally, we use our best implementation to discover 15 better scores for 20 standard SameGame boards. |
Year | DOI | Venue |
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2017 | 10.1007/978-3-319-75931-9_8 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Root Parallelization,Nested Monte-Carlo Search (NMCS),Playout Policy,Hybrid Parallelization Strategy,Transposition Table | Heuristic,Monte Carlo method,Simulation,Computer science,Theoretical computer science,Optimization problem | Conference |
Volume | ISSN | Citations |
818 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 9 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Benjamin Négrevergne | 1 | 35 | 5.44 |
Tristan Cazenave | 2 | 459 | 58.77 |