In the domain of computer games, research into the interaction between player and game
has centred on'enjoyment', often drawing in particular on optimal experience research and …

Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …

This thesis studies the use of Monte-Carlo simulations for tree-search problems. The Monte-
Carlo technique we investigate is Monte-Carlo Tree Search (MCTS). It is a best-first search …

Player behavioural modelling has grown from a means to improve the playing strength of
computer programs that play classic games (eg, chess), to a means for impacting the player …

This paper investigates strategies to generate levels for action-adventure games. For this
genre, level design is more critical than for rule-driven genres such as simulation or rogue …

In previous work we introduced a novel approach to adaptive game AI that was focussed on
the rapid and reliable adaptation to game circumstances. We named the approach 'case …

This research aims at building a preference-based player model of Civilization IV players.
Our model incorporates attributes which are defined for AI players. We use a sequential …

Bridge bidding is considered to be one of the most difficult problems for game-playing
programs. It involves four agents rather than two, including a cooperative agent. In addition …

Poker is a challenging domain that contains both elements of chance and imperfect infor
mation. Though progress has been made in the domain, there is still one major stumbling …

The thesis describes our research results and the development of new AI techniques that
improve the strength of Go programs. In chapter 1, we provide some general background …