2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning最新文献

TeMPS: A Conceptual Framework for Pervasive and Social Games 普遍性和社交性游戏的概念框架

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.40

Hong Guo, Hallvard Trætteberg, Alf Inge Wang, Meng Zhu

引用次数: 34

Learning Programming Concepts through Game Design: A PCT Perspective 通过游戏设计学习编程概念:PCT视角

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.47

Li-Chun Wang, Ming-Puu Chen

引用次数: 8

Extending Google Android's Application as an Educational Tool 扩展Google Android应用程序作为教育工具

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.38

Bian Wu, Alf Inge Wang, Anders Hartvoll Ruud, W. Zhang

引用次数: 22

Recreating Ancient Egyptian Culture in Second Life 在第二人生中重现古埃及文化

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.45

M. Leigh, Mark G. Elwell, Steve Cook

引用次数: 4

Analysis of Seven Important Studies in Research of Joyful Learning and Society 快乐学习与社会研究中的七项重要研究分析

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.30

C. Lin, Eric Zhi-Feng Liu, Ju-Ling Shih

引用次数: 4

A Mobile and Web System with Contextual Familiarity and its Effect on Campus English Learning 情境熟悉的移动网络系统及其对校园英语学习的影响

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.57

Shu-Chen Cheng, Wu-Yuin Hwang, Dunwei Wen, Sheng-Yi Wu, Ching-Hua Hsiehe, Chia-Yu Chen

引用次数: 5

Reactoon: Storytelling in a Tangible Environment 反应:在有形环境中讲故事

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.28

Alexandra Camargo Alves, R. Lopes, P. Matos, L. Velho, Djalma Silva

引用次数: 23

Instructional Simulations for Teaching High School Computer Science Concepts: A Technology Acceptance Perspective 高中计算机科学概念的教学模拟:技术接受的视角

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.46

Ming-Puu Chen, C. Chiu, Cheng-Chih Wu

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引用次数: 5

Multi-objective Evolution of Neural Go Players 神经围棋棋手的多目标进化

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.19

Kar Bin Tan, J. Teo, P. Anthony

{"title":"Multi-objective Evolution of Neural Go Players","authors":"Kar Bin Tan, J. Teo, P. Anthony","doi":"10.1109/DIGITEL.2010.19","DOIUrl":"https://doi.org/10.1109/DIGITEL.2010.19","url":null,"abstract":"Solving multi-objective optimization problems (MOPs) using evolutionary algorithms (EAs) has been gaining a lot of interest recently. Go is a hard and complex board game. Using EAs, a computer may learn to play the game of Go by playing the games repeatedly and gaining the experience from these repeated plays. In this project, artificial neural networks (ANNs) are evolved with the Pareto Archived Evolution Strategies (PAES) for the computer player to automatically learn and optimally play the small board Go game. ANNs will be automatically evolved with the least amount of complexity (number of hidden units) to optimally play the Go game. The complexity of ANN is of particular importance since it will influence the generalization capability of the evolved network. Hence, there are two conflicting objectives in this study; first is maximizing the Go game fitness score and the second is reducing the complexity in the ANN. Several comparative empirical experiments were conducted that showed that the multi-objective optimization with two distinct and conflicting fitness functions outperformed the single-objective optimization which only optimized the first objective with no selection pressure selection on the second objective.","PeriodicalId":430843,"journal":{"name":"2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126466771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Design-Based Action Research in the World of Robot Technology and Learning 机器人技术与学习领域中基于设计的行动研究

2010 Third IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning Pub Date : 2010-04-12 DOI: 10.1109/DIGITEL.2010.21

G. Majgaard

引用次数: 7