Kunstig Intelligens til Brætspillet Taiji - Danmarks Tekniske Universitet

Summary
This project concerns the development of several artificial intelligences to the
board game Taiji. Taiji is a fully observable abstract strategic game where two
opponents each will try to score the most points by forming a larger figure on
the board than the opponent’s figure.
Taiji is a relatively new game released in the year 2007 and therefore there
has not yet been developed an effective artificial intelligence (AI) for the game.
The game’s designer, Néstor Romeral Andrés, has developed a simple AI for the
game, but it requires great computing power at the high difficulty levels without
even necessarily defeating a human opponent.
The project aims to develop an effective AI to Taiji. In the first phase is implemented
a classical AI-based search in a Minimax game tree. This involves,
among other, construction of an appropriate heuristics for the game. The next
stage is to examine further opportunities for improvement and development of
more advanced AI’er. This includes, inter alia, an upgrade from game tree to
game graph. Game tree gives as the name indicates only the opportunity to
follow structure of the path, while the game graph allows move across structure
of the path and thus is considerably more comprehensive.
The project also includes an analysis of the game’s complexity and a score
of winning strategies for different board sizes.
The physical implementation of the game and the artificial intelligences have
been made in Java.