Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

Stephen Muggleton (Author) Other; Aline Paes (Author) Other; Vitor Santos Costa (Author) FCUP; Gerson Zaverucha (Author) Other

Conference proceedings International

Title: INDUCTIVE LOGIC PROGRAMMING

Pages: 123-130

19th International Conference on Inductive Logic Programming

Leuven, BELGIUM, JUL 02-04, 2009

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 12 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-005-5NB

DOI: 10.1007/978-3-642-13840-9_12

Abstract (EN): The game of chess has been a major testbed for research in artificial intelligence, since it requires focus on intelligent reasoning. Particularly, several challenges arise to machine learning systems when inducing a model describing legal moves of the chess, including the collection of the examples, the learning of a model correctly representing the official rules of the game, covering all the branches and restrictions of the correct moves, and the comprehensibility of such a model. Besides, the game of chess has inspired the creation of numerous variants, ranging from faster to more challenging or to regional versions of the game. The question arises if it is possible to take advantage of an initial classifier of chess as a starting point to obtain classifiers for the different variants. We approach this problem as an instance of theory revision from examples. The initial classifier of chess is inspired by a FOL theory approved by a chess expert and the examples are defined as sequences of moves within a game. Starting from a standard revision system, we argue that abduction and negation are also required to best address this problem. Experimental results show the effectiveness of our approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8