Games solved: Now and in the future

@article{Herik2002GamesSN,
  title={Games solved: Now and in the future},
  author={H. Jaap van den Herik and Jos Uiterwijk and Jack van Rijswijck},
  journal={Artif. Intell.},
  year={2002},
  volume={134},
  pages={277-311}
}
Solving games: Dependence of applicable solving procedures
Paranoid Proof-Number Search
TLDR
This work proposes and introduces and examines an algorithm, called Paranoid Proof-Number Search (PPNS), for solving multi-player games under the paranoid condition, and shows that for Rolit PPNS is taking advantage of the non-uniformity of the game tree.
Solving Games and All That
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This work presents a formal framework to represent best-first search algorithms, and proposes an extension of this technique for stacked-matrix games, a generalization of zero-sum perfect information two-player games that allows simultaneous moves.
Computing Games: Bridging the Gap Between Search and Entertainment
TLDR
The probability-based proof number search (PPNS) and single conspiracy number (SCN) were used as the domain-independent indicators to analyze how uncertainty affects various game elements and demonstrate the link between the search indicators and the measure of entertainment where uncertainty plays a vital role in both contexts.
Monte-Carlo Search Techniques in the Modern Board Game Thurn and Taxis
TLDR
This thesis investigates the effectiveness of Monte-Carlo Tree Search when applied to a modern board game, for which the board game Thurn and Taxis was used, and can conclude that Monte- Carlo Tree Search gives a slight performance increase over standard Monte- carlo search.
Ph D in Computer Games and Artificial Intelligence
TLDR
The first aim of the PhD thesis is to explore Machine Learning techniques (ML) such as Evolutionary Computation (EC) or Reinforcement Learning (RL) using high complexity games as testbeds and to build strong game playing programs in using ML techniques.
Solving Strong and Weak 4-in-a-Row
  • J. Uiterwijk
  • Mathematics
    2019 IEEE Conference on Games (CoG)
  • 2019
TLDR
The monotonicity property of winning positional games, widely believed to hold for rectangular boards, is not true, at least not for arbitrary positions on a rectangular board, and it is shown that the 5×6 board indeed is a monotone win.
An Intelligent Artificial Player for the Game of Risk
TLDR
The results of this work imply the presumption that dynamic, player-defined high-level goals in combination with temporal difference learning may yield a very strong artificial player.
A method to construct knowledge table-base in k-in-a-row games
TLDR
It is found it is a good method to decrease the complexity of the k-in-a-row games by using Connection to represent the states of the game position, and a precise classification criterion for Connection, as well as a precise classified for the intersections is given.
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