Modeling expert players´ behavior through data mining

Author

Acuna, Daniel ; Parada, Víctor

Author_Institution

Departamento de Ingenieria Informdtica, Univ. de Santiago de Chile, Chile

fYear

2005

fDate

7-11 Nov. 2005

Abstract

Games are a field in which players are implicitly trained and compelled to solve hard problems optimally. By making an appropriate training experiment using a computer game, players can reach expert performance. A computer game tournament that contains Euclidian traveling salesman problem (ETSP) instances is developed and solutions made by expert players are analyzed with human-behavior hypotheses and data mining techniques. A model for the expert players´ behavior that combines apparently different fields is proposed and tested with TSPLIB problems.

Keywords

behavioural sciences computing; cognition; computer games; data mining; travelling salesman problems; Euclidian traveling salesman problem; cognitive modeling; computer game tournament; data mining; expert player behavior modeling; games; heuristics; human-behavior hypotheses; human-problem solving; Artificial intelligence; Data mining; Decision trees; Humans; Industrial training; Machine intelligence; Management training; NP-complete problem; Pattern recognition; Systems engineering and theory; Cognitive modeling; data mining; heuristics; human-problem solving;

fLanguage

English

Publisher

ieee

Conference_Titel

Chilean Computer Science Society, 2005. SCCC 2005. 25th International Conference of the

ISSN

1522-4902

Print_ISBN

0-7695-2491-5

Type

conf

DOI

10.1109/SCCC.2005.1587866

Filename

1587866