Solving Raven's IQ-tests: An AI and Cognitive Modeling Approach

机译：解决Raven的智商测试：一种AI和认知建模方法

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Human reasoners have an impressive ability to solve analogical reasoning problems and they still outperform computational systems. Analogical reasoning is relevant in dealing with intelligence tests. There are two kinds of approaches: to solve IQ-test problems in a way similar to humans (i.e., a cognitive approach) or to solve these problems optimally (i.e., the AI approach). Most systems can be associated with one of these approaches. Detailed systems solving geometrical intelligence tests, explaining cognitive operations based on working memory and producing precise predictions and results such as error rates and response times have not been developed so far. We present a system implemented in the cognitive architecture ACT-R, able to solve analogously developed problems of Raven's Standard and Advanced Progressive Matrices. The model solves 66 of the 72 tested problems of both tests. The model's predicted error rates correlate to human performance with r - .8 for the Advanced Progressive Matrices and r = .7 for all problems together.

机译：人类推理机具有解决类比推理问题的出色能力，但仍胜过计算系统。类比推理与处理智力测验有关。有两种方法：以类似于人类的方式解决智商测试问题（即认知方法）或以最佳方式解决这些问题（即AI方法）。大多数系统可以与这些方法之一相关联。到目前为止，尚未开发出解决几何智能测试，解释基于工作记忆的认知操作以及产生精确的预测和结果（例如错误率和响应时间）的详细系统。我们提出了在认知体系ACT-R中实现的系统，该系统能够解决Raven标准和高级渐进矩阵的类似开发问题。该模型解决了两个测试的72个测试问题中的66个。该模型的预测错误率与人类绩效相关，高级进阶矩阵的r-.8，所有问题的r = .7。

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《20th European conference on artificial intelligence》|2012年|666-671|共6页
会议地点 Montpellier(FR)
作者
Marco Ragni; Stefanie Neubert;
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University of Freiburg, Germany;

University of Freiburg, Germany;

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正文语种 eng
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1. Solving the Raven Progressive Matrices by adults with intellectual disability with/without Down syndrome: Different cognitive patterns as indicated by eye-movements [J] . VakilE., Lifshitz-ZehaviH. Research in developmental disabilities . 2012,第2期

机译：患有/不患有唐氏综合症的智障成人解决乌鸦进行性矩阵：眼动表明不同的认知模式
2. A computational model for solving problems from the Raven's Progressive Matrices intelligence test using iconic visual representations [J] . Maithilee Kunda, Keith McGreggor, Ashok K. Goel Cognitive Systems Research . 2013,第JUNa期

机译：使用图标视觉表示解决Raven渐进矩阵智能测试中的问题的计算模型
3. A spiking neural model applied to the study of human performance and cognitive decline on Raven's Advanced Progressive Matrices [J] . Daniel Rasmussen, Chris Eliasmith Intelligence: A Multidisciplinary Journal . 2014,第Null期

机译：尖峰神经模型用于研究Raven高级进阶矩阵的人类表现和认知能力下降
4. Solving Raven's IQ-tests: An AI and Cognitive Modeling Approach [C] . Marco Ragni, Stefanie Neubert European Conference on Artificial Intelligence . 2012

机译：解决乌鸦的智商测试：AI和认知建模方法
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KKT is a science wing that tries to solve human problems with a wider perspective aimed at solving problematic human behaviors (Plumb, Stewart, Dahl and Lundgren, 2009). It is seen that there is very little research about the new approach of ACT approach when the aiming country of our country is screened and it is thought that our country will contribute to the field of psychological counseling with the work done. In the scope of the research, experimental and control groups and preliminary test, post-test and follow-up measurements of 2x3 experimental design were used. The study's study group consists of a total of 24 (12 experimental and 12 control groups) university students studying in different departments and levels, continuing their education in the academic year of 2015-2016 in Ağrı province and İbrahim Chechen University in 2015-2016 academic year. The average age of participants in the experiment and control group is 20. 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Solving Raven's IQ-tests: An AI and Cognitive Modeling Approach

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