Learning Minesweeper with Multirelational Learning Export

@misc{citeulike:767959, abstract = {Minesweeper is a one-person game which looks deceptively easy to play, but where average human performance is far from optimal. Playing the game requires logical, arithmetic and probabilistic reasoning based on spatial relationships on the board. Simply checking a board state for consistency is an NP-complete problem. Given the difficulty of hand-crafting strategies to play this and other games, AI researchers have always been interested in automatically learning such strategies from...}, author = {Castillo, Lourdes P. and Wrobel, Stefan}, citeulike-article-id = {767959}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.2737}, keywords = {inductive-logic-programming, machine-learning}, posted-at = {2006-07-21 08:10:27}, priority = {0}, title = {Learning Minesweeper with Multirelational Learning}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.2737} }

TY - GEN ID - citeulike:767959 L3 - citeulike-article-id:767959 N2 - Minesweeper is a one-person game which looks deceptively easy to play, but where average human performance is far from optimal. Playing the game requires logical, arithmetic and probabilistic reasoning based on spatial relationships on the board. Simply checking a board state for consistency is an NP-complete problem. Given the difficulty of hand-crafting strategies to play this and other games, AI researchers have always been interested in automatically learning such strategies from... TI - Learning Minesweeper with Multirelational Learning KW - inductive-logic-programming KW - machine-learning AU - Castillo, Lourdes AU - Wrobel, Stefan UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.2737 ER -