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A Neural Network May Show the Best Way to Learn How to Count for Students in Elementary Math Courses 神经网络可能为小学数学课程的学生展示学习如何计数的最佳方法
2008 Seventh Mexican International Conference on Artificial Intelligence Pub Date : 2008-10-27 DOI: 10.1109/MICAI.2008.47
A. Neme, V. Carrión, A. Muoz, P. Miramontes, A. Cervera
{"title":"A Neural Network May Show the Best Way to Learn How to Count for Students in Elementary Math Courses","authors":"A. Neme, V. Carrión, A. Muoz, P. Miramontes, A. Cervera","doi":"10.1109/MICAI.2008.47","DOIUrl":"https://doi.org/10.1109/MICAI.2008.47","url":null,"abstract":"Learning how to count in different bases has been seen as a trivial task in almost all introductory mathematics courses. However, the low performance shown by many students, while performing this task, is appalling. This situation has motivated serious research in this matter. In order to study a model of count learning, we analyze the performance of a multilayer perceptron that learns to count in several bases (5, 10, 13, 20, 60). We give evidence that it is not equivalent for the model to learn to count in all base as the errors are not equivalent, biased toward a low error when the task is to learn to count in base 20. When the task is to learn to count in all bases following a given sequence, the model shows non-equivalent errors for some bases. This may shed some light on education planning that can result in better introductory courses.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128229325","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: 0
Geometric Tools for Perspective Taking for Human–Robot Interaction 人机交互视角的几何工具
2008 Seventh Mexican International Conference on Artificial Intelligence Pub Date : 2008-10-27 DOI: 10.1109/MICAI.2008.40
Luis Felipe, Marin-Urias, E. Akin Sisbot, Rachid Alami
{"title":"Geometric Tools for Perspective Taking for Human–Robot Interaction","authors":"Luis Felipe, Marin-Urias, E. Akin Sisbot, Rachid Alami","doi":"10.1109/MICAI.2008.40","DOIUrl":"https://doi.org/10.1109/MICAI.2008.40","url":null,"abstract":"Psychological studies on human interactions made surface the notion perspective taking. This notion, referring to reason on other persons' points of view, eases the communication between interacting individuals. For a robot interacting with people, we believe that perspective taking can play an important role that will allow the robot to understand, reason and act according to human's point of view thus allowing an efficient communication and cooperation. In this paper, we propose a group of algorithms to evaluate and generate robot configurations that are not only collision free but also obeying HRI constraints by reasoning explicitly on human's perspective.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131461014","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: 24
Boosting for Image Interpretation by Using Natural Features 基于自然特征的图像解译增强
2008 Seventh Mexican International Conference on Artificial Intelligence Pub Date : 2008-10-27 DOI: 10.1109/MICAI.2008.62
J. Aviña-Cervantes, M. Estudillo-Ayala, S. Ledesma-Orozco, M. Ibarra-Manzano
{"title":"Boosting for Image Interpretation by Using Natural Features","authors":"J. Aviña-Cervantes, M. Estudillo-Ayala, S. Ledesma-Orozco, M. Ibarra-Manzano","doi":"10.1109/MICAI.2008.62","DOIUrl":"https://doi.org/10.1109/MICAI.2008.62","url":null,"abstract":"In this paper a research in classification of natural images by using Adaboost (adapting boosting) method is presented. This technique is used to identify the nature of the main regions in the image, that is, to identify if they are roads, trees, shades, sky, bushes or others interesting regions; image is previously segmented and each of its regions are represented by a R12 data vector (including features as color, texture and context), in at least 5 classes. The proposed methodology is presented for a multi-class classification problem and for validating our results, performances ratios between Adaboost and the support vector machines are discussed. This methodology is intent to be applied in medical imagery and in visual based navigation on natural environments; in robot navigation, very good results are obtained even in poorly color saturated images. Finally, the results are described and presented showing that Adaboost is a reliable classification technique giving slightly better performances than SVM for regions in natural images.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124479052","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: 6
In Search of an Optimal Set of Images for Uncalibrated Photometric Stereo 寻找一组最佳图像用于未校准的光度立体
2008 Seventh Mexican International Conference on Artificial Intelligence Pub Date : 2008-10-27 DOI: 10.1109/MICAI.2008.60
F. Hernández-Rodríguez, Mario Castelán
{"title":"In Search of an Optimal Set of Images for Uncalibrated Photometric Stereo","authors":"F. Hernández-Rodríguez, Mario Castelán","doi":"10.1109/MICAI.2008.60","DOIUrl":"https://doi.org/10.1109/MICAI.2008.60","url":null,"abstract":"In this paper, we draw on the ideas of previous work done by Drbohlav and Chantler [5], where a theoretical study on the optimal lighting configuration for photometric stereo was developed. They demonstrated that the known n light source azimuth angles should be equally spaced over 360/n degrees and the n light source elevation angles should be constant. In this paper, our aim is to develop a method to find a set of images that best satisfies this lighting configuration, assuming that light source directions are unknown. To this end, we estimate lighting coefficients using a harmonic spherical illumination model and a reference surface. Once the set of light source directions is estimated, we select those images that best satisfy the optimal lighting configuration. Experiments on face datasets show that the selected images are the most suitable for the purposes of calculation of height maps through surface integration.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129727113","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: 1
Implementation of Emotional Learning for Cognitive Tutoring Agents 认知辅导代理的情绪学习实现
2008 Seventh Mexican International Conference on Artificial Intelligence Pub Date : 2008-10-27 DOI: 10.1109/MICAI.2008.45
U. Faghihi, P. Poirier, D. Dubois, M. Gaha, R. Nkambou
{"title":"Implementation of Emotional Learning for Cognitive Tutoring Agents","authors":"U. Faghihi, P. Poirier, D. Dubois, M. Gaha, R. Nkambou","doi":"10.1109/MICAI.2008.45","DOIUrl":"https://doi.org/10.1109/MICAI.2008.45","url":null,"abstract":"We here describe some essential and fundamental learning mechanisms, both \"conscious and unconscious\". The proposed architecture is based on functional \"consciousness\" mechanisms. In this paper, we suggest an emotional learning mechanism (ELM) model, which can both learn new events and influence different types of \"conscious\" and \"unconscious\" learning. This will increase the agent's autonomy in unknown or changing environments, and thus improve its fitness. This architecture is inspired by mechanisms believed to exist in humans [6].","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126236502","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: 5
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