Teachable characters: Semantic neural networks in game AI

被引：0
作者：
Ketamo, Harri [1 ]
机构：
[1] Satakunta Univ Appl Sci, FIN-28600 Pori, Finland
来源：
NN'09: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON NEURAL NETWORKS: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON NEURAL NETWORKS (NN'09) | 2009年
关键词：
Game AI; Reinforcement learning; Conceptual learning; Semantic networks; Serious games;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The aim of the study was to apply machine learning into educational game and evaluate the Outcome in context of cognitive psychology of learning. The Study was done in two phases: design phase and evaluation phase (N=59). The design of the game was done in order to support relatively free teaching of a Virtual pet in an easy-to-use environment. The main finding of the study was a clear causality between quality of teaching in game world and players' knowledge in real life.
引用
收藏
页码：11 / 16
页数：6
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