Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622241
M. Monwar, B. Kumar, Vishnu Naresh Boddeti, J. Smereka
Under challenging imaging conditions which include lower resolution, occlusion, motion and de-focus blur, iris recognition performance degrades. In such conditions ocular region has been suggested as a new biometric modality which has the ability to overcome some of the above mentioned drawbacks. In this work, we investigate the performance of rank level fusion approach that fuses the outputs of three ocular region matching algorithms, namely, Probabilistic Deformation Model (PDM), modified Scale-Invariant Feature Transform (m-SIFT) and Gradient Orientation Histogram (GOH), employed for recognizing challenging ocular images in the Face and Ocular Challenge Series (FOCS) dataset. We investigate different rank fusion schemes including the highest rank, Borda count, plurality voting and Markov chain and demonstrate that rank-level fusion can lead to improved recognition performance.
{"title":"Rank information fusion for challenging ocular image recognition","authors":"M. Monwar, B. Kumar, Vishnu Naresh Boddeti, J. Smereka","doi":"10.1109/ICCI-CC.2013.6622241","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622241","url":null,"abstract":"Under challenging imaging conditions which include lower resolution, occlusion, motion and de-focus blur, iris recognition performance degrades. In such conditions ocular region has been suggested as a new biometric modality which has the ability to overcome some of the above mentioned drawbacks. In this work, we investigate the performance of rank level fusion approach that fuses the outputs of three ocular region matching algorithms, namely, Probabilistic Deformation Model (PDM), modified Scale-Invariant Feature Transform (m-SIFT) and Gradient Orientation Histogram (GOH), employed for recognizing challenging ocular images in the Face and Ocular Challenge Series (FOCS) dataset. We investigate different rank fusion schemes including the highest rank, Borda count, plurality voting and Markov chain and demonstrate that rank-level fusion can lead to improved recognition performance.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123611840","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622239
Orhan Firat, M. Ozay, Itir Önal, Ilke Öztekin, F. Yarman-Vural
We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning machine, local meshes are formed around each voxel. The distance between voxels in the mesh is determined by using functional neighborhood concept. In order to define functional neighborhood, the similarities between the time series recorded for voxels are measured and functional connectivity matrices are constructed. Then, the local mesh for each voxel is formed by including the functionally closest neighboring voxels in the mesh. The relationship between the voxels within a mesh is estimated by using a linear regression model. These relationship vectors, called Functional Connectivity aware Local Relational Features (FC-LRF) are then used to train a statistical learning machine. The proposed method was tested on a recognition memory experiment, including data pertaining to encoding and retrieval of words belonging to ten different semantic categories. Two popular classifiers, namely k-Nearest Neighbor and Support Vector Machine, are trained in order to predict the semantic category of the item being retrieved, based on activation patterns during encoding. The classification performance of the Functional Mesh Learning model, which range in 62-68% is superior to the classical multi-voxel pattern analysis (MVPA) methods, which range in 40-48%, for ten semantic categories.
{"title":"Functional Mesh Learning for pattern analysis of cognitive processes","authors":"Orhan Firat, M. Ozay, Itir Önal, Ilke Öztekin, F. Yarman-Vural","doi":"10.1109/ICCI-CC.2013.6622239","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622239","url":null,"abstract":"We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning machine, local meshes are formed around each voxel. The distance between voxels in the mesh is determined by using functional neighborhood concept. In order to define functional neighborhood, the similarities between the time series recorded for voxels are measured and functional connectivity matrices are constructed. Then, the local mesh for each voxel is formed by including the functionally closest neighboring voxels in the mesh. The relationship between the voxels within a mesh is estimated by using a linear regression model. These relationship vectors, called Functional Connectivity aware Local Relational Features (FC-LRF) are then used to train a statistical learning machine. The proposed method was tested on a recognition memory experiment, including data pertaining to encoding and retrieval of words belonging to ten different semantic categories. Two popular classifiers, namely k-Nearest Neighbor and Support Vector Machine, are trained in order to predict the semantic category of the item being retrieved, based on activation patterns during encoding. The classification performance of the Functional Mesh Learning model, which range in 62-68% is superior to the classical multi-voxel pattern analysis (MVPA) methods, which range in 40-48%, for ten semantic categories.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128539582","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622228
Padma Polash Paul, M. Gavrilova
Multimodal biometric system has emerged as a highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. The idea behind the cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, we present a novel architecture for template generation within the context of the cancelable multimodal system. We develop a novel cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. We further validate the performance of the proposed algorithm on a virtual multimodal face and ear database.
{"title":"Novel multimodal template generation algorithm","authors":"Padma Polash Paul, M. Gavrilova","doi":"10.1109/ICCI-CC.2013.6622228","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622228","url":null,"abstract":"Multimodal biometric system has emerged as a highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. The idea behind the cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, we present a novel architecture for template generation within the context of the cancelable multimodal system. We develop a novel cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. We further validate the performance of the proposed algorithm on a virtual multimodal face and ear database.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130542399","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622270
Mo Xia, Mian Sun, G. Luo, Xibin Zhao
Programmable Logic Controller (PLC) have been widely used in industries, and safety and reliability of them has been urgently concerned. However, it's hard to verify all the cases to discover the logical flaws of complex systems by traditional testing. Formal verification methods introduce mathematical rigor in their analysis thereby guaranteeing exhaustive state space coverage. But there is not an effective and efficient tool for PLC verification, and the general-purpose formal tools need lots of relevant knowledge. This paper proposes an automatic verification tool for PLC systems. It includes graphical modeling, syntax check, code generation, code optimization and representation of the counter-examples which violate some system properties.
{"title":"Design and implementation of automatic verification for PLC systems","authors":"Mo Xia, Mian Sun, G. Luo, Xibin Zhao","doi":"10.1109/ICCI-CC.2013.6622270","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622270","url":null,"abstract":"Programmable Logic Controller (PLC) have been widely used in industries, and safety and reliability of them has been urgently concerned. However, it's hard to verify all the cases to discover the logical flaws of complex systems by traditional testing. Formal verification methods introduce mathematical rigor in their analysis thereby guaranteeing exhaustive state space coverage. But there is not an effective and efficient tool for PLC verification, and the general-purpose formal tools need lots of relevant knowledge. This paper proposes an automatic verification tool for PLC systems. It includes graphical modeling, syntax check, code generation, code optimization and representation of the counter-examples which violate some system properties.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"552 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116236114","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622291
Guo-Cheng Lan, T. Hong, Pei-Shan Wu, S. Tsumoto
Different from the existing studies, this work presents a new kind of rules with the concept of a hierarchy of time granules, namely hierarchical temporal association rules. The lifespan of an item in a time granule is calculated from the publication time of the item to the end time in the time granule. A three-phase mining framework is proposed to effectively and efficiently find this kind of rules from a temporal database. The experimental results show the performance of the proposed algorithm under the item lifespan definition.
{"title":"Mining hierarchical temporal association rules in a publication database","authors":"Guo-Cheng Lan, T. Hong, Pei-Shan Wu, S. Tsumoto","doi":"10.1109/ICCI-CC.2013.6622291","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622291","url":null,"abstract":"Different from the existing studies, this work presents a new kind of rules with the concept of a hierarchy of time granules, namely hierarchical temporal association rules. The lifespan of an item in a time granule is calculated from the publication time of the item to the end time in the time granule. A three-phase mining framework is proposed to effectively and efficiently find this kind of rules from a temporal database. The experimental results show the performance of the proposed algorithm under the item lifespan definition.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132527620","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622249
Tse-Yi Wang, Yen-Ho Chen, Kuang-Chi Chen
Although genome-wide association studies report many disease-associated loci involved in pathogenesis, current identified variants only explain a little part of the heritability underlying complex diseases. To explore the other missing part of heritability, data-mining methods are proposed and developed to detect disease-associated interactions between variants. Recently, some studies have revealed the linkage disequilibrium between chromosome structure variations and disease-associated loci. We are motivated to employ a fusion approach that incorporates the information of copy number variations (CNVs) for identifying interactions between single nucleotide polymorphisms (SNPs). The CNV profiles are first used for clustering analysis of disease subtypes, and then the SNP-SNP interactions are examined by the multifactor dimensionality reduction (MDR) method. We applied the fusion approach in analyzing 214 lymphoma cases. The results showed that the interactions identified by the fusion approach were more significantly associated with lymphoma than those identified only by MDR without incorporating CNV information. Therefore, we conclude that information fusion of CNVs and SNPs provides a proper strategy for detecting gene-gene interactions in disease association studies.
{"title":"Information fusion of CNVs and SNPs on gene-gene interactions for molecular subtypes of lymphoma","authors":"Tse-Yi Wang, Yen-Ho Chen, Kuang-Chi Chen","doi":"10.1109/ICCI-CC.2013.6622249","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622249","url":null,"abstract":"Although genome-wide association studies report many disease-associated loci involved in pathogenesis, current identified variants only explain a little part of the heritability underlying complex diseases. To explore the other missing part of heritability, data-mining methods are proposed and developed to detect disease-associated interactions between variants. Recently, some studies have revealed the linkage disequilibrium between chromosome structure variations and disease-associated loci. We are motivated to employ a fusion approach that incorporates the information of copy number variations (CNVs) for identifying interactions between single nucleotide polymorphisms (SNPs). The CNV profiles are first used for clustering analysis of disease subtypes, and then the SNP-SNP interactions are examined by the multifactor dimensionality reduction (MDR) method. We applied the fusion approach in analyzing 214 lymphoma cases. The results showed that the interactions identified by the fusion approach were more significantly associated with lymphoma than those identified only by MDR without incorporating CNV information. Therefore, we conclude that information fusion of CNVs and SNPs provides a proper strategy for detecting gene-gene interactions in disease association studies.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134076842","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622251
H. Hara
In this paper, Design of a concept of a Symbiotic Sensor Network (SSN) and its implementation methodology are proposed. SSN can support people who install sensor network into ordinary home with 1)autonomous action and 2)interactive function.
{"title":"Design of a Symbiotic Sensor Network","authors":"H. Hara","doi":"10.1109/ICCI-CC.2013.6622251","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622251","url":null,"abstract":"In this paper, Design of a concept of a Symbiotic Sensor Network (SSN) and its implementation methodology are proposed. SSN can support people who install sensor network into ordinary home with 1)autonomous action and 2)interactive function.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116098661","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622264
Wei Wu, Li Li
The current automated Chinese-English translation scoring methods mainly fall into two categories: one is based on the text similarity and the other on Natural Language Process (NLP). Both of them have to face the problem in their accuracy. This paper proposed an automated Chinese-English translation scoring method based on answer knowledge base by analyzing the shortcomings of the current automated scoring methods of Chinese-English translation. Answer knowledge base is constructed by means of such methods as semantic expansion of the answers. Students' answers are automatically scored based on the answer knowledge base, which improves its adaptability, flexibility and accuracy. The analysis of contrast experiments indicates that the method can work well and its accuracy is obviously improved. Meanwhile, this method can also apply to the automated scoring in other subjective tests.
{"title":"Automated Chinese-English translation scoring based on answer knowledge base","authors":"Wei Wu, Li Li","doi":"10.1109/ICCI-CC.2013.6622264","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622264","url":null,"abstract":"The current automated Chinese-English translation scoring methods mainly fall into two categories: one is based on the text similarity and the other on Natural Language Process (NLP). Both of them have to face the problem in their accuracy. This paper proposed an automated Chinese-English translation scoring method based on answer knowledge base by analyzing the shortcomings of the current automated scoring methods of Chinese-English translation. Answer knowledge base is constructed by means of such methods as semantic expansion of the answers. Students' answers are automatically scored based on the answer knowledge base, which improves its adaptability, flexibility and accuracy. The analysis of contrast experiments indicates that the method can work well and its accuracy is obviously improved. Meanwhile, this method can also apply to the automated scoring in other subjective tests.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128038599","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622257
K. Fujimoto
Electronic word-of-mouth (eWOM) is an important information source that influences consumer product evaluations. The author previously developed a computational model, called an inference space model, that predicts potency-magnitude relations of eWOM messages involving subjective rank expressions, which refer to the linguistic representations related to the attitude-levels of the benefits of product attributes. This paper mathematically investigates the potencymagnitude relations of message types differentiating the attitude direction and the strength. The investigations include the developments of a Q-magnitude Relation Map (Q-Map) which illustrates how the relations change based on the values of two parameters: evaluation target size and scale-size balancing indicator. The results show that three scale-classes of bipolar rating scales have a critical role in knowing how the relations change. Based on observations of the Q-Maps, unexplored hypotheses on the potency-magnitude relations are developed with respect to messages involving attitude direction without its strength.
{"title":"Characterizing bipolar rating scales to investigate potency of eWOM messages involving attitude directionwithout its strength","authors":"K. Fujimoto","doi":"10.1109/ICCI-CC.2013.6622257","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622257","url":null,"abstract":"Electronic word-of-mouth (eWOM) is an important information source that influences consumer product evaluations. The author previously developed a computational model, called an inference space model, that predicts potency-magnitude relations of eWOM messages involving subjective rank expressions, which refer to the linguistic representations related to the attitude-levels of the benefits of product attributes. This paper mathematically investigates the potencymagnitude relations of message types differentiating the attitude direction and the strength. The investigations include the developments of a Q-magnitude Relation Map (Q-Map) which illustrates how the relations change based on the values of two parameters: evaluation target size and scale-size balancing indicator. The results show that three scale-classes of bipolar rating scales have a critical role in knowing how the relations change. Based on observations of the Q-Maps, unexplored hypotheses on the potency-magnitude relations are developed with respect to messages involving attitude direction without its strength.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130906445","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}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622232
José-Antonio Cervantes, Luis-Felipe Rodríguez, Sonia López, Félix F. Ramos
In areas such as psychology and neuroscience a common approach to study human behavior has been the development of theoretical models of cognition. In fields such as artificial intelligence, these cognitive models are usually translated into computational implementations and incorporated into the architectures of intelligent autonomous agents (AAs). The main assumption is that this design approach contributes to the development of intelligent systems capable of displaying very believable and human-like behaviors. Decision Making is one of the most investigated and computationally implemented cognitive functions. The literature reports several computational models designed to allow AAs to make decisions that help achieve their personal goals and needs. However, most models disregard crucial aspects of human decision making such as other agents' needs, ethical values, and social norms. In this paper, we propose a biologically inspired computational model of Moral Decision Making (MDM). This model is designed to enable AAs to make decisions based on ethical and moral judgment. The simulation results demonstrate that the model helps to improve the believability of virtual agents when facing moral dilemmas.
{"title":"A biologically inspired computational model of Moral Decision Making for autonomous agents","authors":"José-Antonio Cervantes, Luis-Felipe Rodríguez, Sonia López, Félix F. Ramos","doi":"10.1109/ICCI-CC.2013.6622232","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622232","url":null,"abstract":"In areas such as psychology and neuroscience a common approach to study human behavior has been the development of theoretical models of cognition. In fields such as artificial intelligence, these cognitive models are usually translated into computational implementations and incorporated into the architectures of intelligent autonomous agents (AAs). The main assumption is that this design approach contributes to the development of intelligent systems capable of displaying very believable and human-like behaviors. Decision Making is one of the most investigated and computationally implemented cognitive functions. The literature reports several computational models designed to allow AAs to make decisions that help achieve their personal goals and needs. However, most models disregard crucial aspects of human decision making such as other agents' needs, ethical values, and social norms. In this paper, we propose a biologically inspired computational model of Moral Decision Making (MDM). This model is designed to enable AAs to make decisions based on ethical and moral judgment. The simulation results demonstrate that the model helps to improve the believability of virtual agents when facing moral dilemmas.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131145819","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：