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researcher

Mark H. M. Winands

2 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author1

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.AI2
ORCID 0000-0002-0125-0824

identity via Semantic Scholar / OpenAlex

most citedMonte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups

6 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2021

Split Moves for Monte-Carlo Tree Search

Jakub Kowalski, Maksymilian Mika, Wojciech Pawlik +3

In many games, moves consist of several decisions made by the player. These decisions can be viewed as separate moves, which is already a common practice in multi-action games for…

cs.AI2014★ 6 cited

Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups

Marc Lanctot, Mark H. M. Winands, Tom Pepels +1

Monte Carlo Tree Search (MCTS) has improved the performance of game engines in domains such as Go, Hex, and general game playing. MCTS has been shown to outperform classic alpha-be…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.