Most research in computer chess has focussed on creating an excellent chess player, with relatively little concern given to modelling how humans play chess. The research reported in this paper is aimed at investigating knowledge-based chess in the context of building a prototype chess tutor, UMRAO, which helps students learn how to play bishop-pawn endgames. In tutoring it is essential to take ...

For many years, those who care about promoting health acted as though cigarettes fell from the sky and our job was merely to keep kids from picking them up while telling those who did that it was bad for them. Some still see it that way. But the end of the last century pulled back the curtain on the tobacco industry and its global conspiracy to protect its profits at the expense of millions of ...

We investigate a strong chess endgame player, previously evolved by us through genetic programming [1]. Its performance is analyzed across four games, demonstrating the chess-playing capabilities developed through evolution. We end with a discussion of our GP-evolved player’s pros and cons.

BACKGROUND There is increasing interest in ending the tobacco epidemic and in applying 'endgame' solutions to achieve that goal at national levels. We explored the understanding of, and reactions to, a tobacco-free vision and an endgame approach to tobacco control among New Zealand smokers and non-smokers. METHODS We recruited participants in four focus groups held in June 2009: Māori (indige...

Using full-game databases and optimized tree-search algorithms, the game of Kalah is solved for several starting configurations up to 6 holes and 5 counters per hole. The main search algorithm used was iterative-deepening MTD(f). Major search enhancements were move ordering, transposition tables, futility pruning, enhanced transposition cut-off, and endgame databases.