P. Spronck

Publications172
h-index28
Citations3,041
Highly Influential Citations167
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Monte-Carlo Tree Search: A New Framework for Game AI
TLDR
This paper puts forward Monte-Carlo Tree Search as a novel, unified framework to game AI, and demonstrates that it can be applied effectively to classic board- games, modern board-games, and video games.
Adaptive game AI with dynamic scripting
TLDR
It is concluded that dynamic scripting can be successfully applied to the online adaptation of game AI in commercial computer games by implementing the technique in the game Neverwinter Nights.
Monte-Carlo Tree Search in Settlers of Catan
TLDR
It is shown that MCTS can be adapted successfully to multi-agent environments, and the results show that the agent has a considerable playing strength when compared to game implementation with existing heuristics.
Adaptive game AI
Auditing in Egypt: A study of the legal framework and professional standards
The objective of the paper is to present an analysis of the legal framework surrounding the auditing profession in Egypt, and the problems faced by the profession. The basic Company Law of 1951 and…
DIFFICULTY SCALING OF GAME AI
TLDR
It is concluded that dynamic scripting, using top culling, can enhance the entertainment value of games by scaling the difficulty level of the game AI to the playing skill of the human player.
Player Modeling
TLDR
This chapter introduces a holistic view of player modeling and provides a high level taxonomy and discussion of the key components of a player’s model, and focuses on a taxonomy of approaches for constructing a player model.
Player behavioural modelling for video games
On-Line Adaptation of Game Opponent AI in Simulation and in Practice
TLDR
It is concluded that dynamic scripting can be successfully applied to the online adaptation of computer game opponent AI and is proposed as a novel technique called “dynamic scripting” that meets these requirements.
Opponent Modeling in Real-Time Strategy Games
TLDR
An approach of opponent modeling based on hierarchically structured models that can be successfully used to classify the strategy of an opponent in the RTS game Spring is proposed.
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