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2012 IEEE 24th International Conference on Tools with Artificial Intelligence最新文献

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Partially Observable Gene Regulatory Network Control without a Boundary on Horizon 无边界的部分可观察基因调控网络控制
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.20
U. Erdogdu, Faruk Polat, R. Alhajj
{"title":"Partially Observable Gene Regulatory Network Control without a Boundary on Horizon","authors":"U. Erdogdu, Faruk Polat, R. Alhajj","doi":"10.1109/ICTAI.2012.20","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.20","url":null,"abstract":"Gene regulatory networks (GRNs) govern the protein transcription process in the cell and interactions among genes play a vital role in determining the biosynthesis rate of proteins. By using intervention techniques discovered by biological research it is possible to control a GRN, thus promoting or demoting the expression rate of a certain gene. In this work, this control task is studied in a partially observable setting where interventions lack perfect knowledge of the expression level of all genes. Moreover, we formulated the task as a lifelong control problem and developed a more flexible and scalable method than the alternatives described in the literature.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122569589","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: 2
Land Use Cartography from Hyperion Hyperspectral Imagery Analysis: Results from a Mediterranean Site 来自Hyperion高光谱图像分析的土地利用制图:来自地中海站点的结果
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.184
G. Petropoulos, K. Arvanitis, N. Sigrimis, D. Piromalis, A. K. Boglou
{"title":"Land Use Cartography from Hyperion Hyperspectral Imagery Analysis: Results from a Mediterranean Site","authors":"G. Petropoulos, K. Arvanitis, N. Sigrimis, D. Piromalis, A. K. Boglou","doi":"10.1109/ICTAI.2012.184","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.184","url":null,"abstract":"Land cover is a fundamental variable of the Earth's system intimately connected with many parts of the human and physical environment. Recent advances in remote sensor technology have led to the launch of spaceborne hyperspectral remote sensing sensors, such as Hyperion. The present study is exploring the potential of Hyperion hyperspectral imagery combined with the Spectral Angle Mapper (SAM) and Support Vectors Machine (SVMs) pixel-based classifiers in obtaining land cover cartography. A typical Mediterranean setting was selected as a case study, located close to the capital of Greece. Validation of the derived thematic maps was performed on the basis of the error matrix statistics using for consistency the same set of validation points. Both classifiers produced generally reasonable results with the SVMs however significantly outperforming the SAM in both overall classification accuracy and kappa coefficient. The higher classification accuracy by SVMs was attributed principally to the classifier ability to identify an optimal separating hyperplane for classes' separation which allows a low generalization error, thus producing the best possible classes' separation. Yet, as a shortcoming of both classifiers was that none of them operates on a sub-pixel level, that potentially reduces their accuracy as a result of spectral mixing problems that can be commonly found in coarse spatial resolution imagery and at fragmented landscapes.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126173896","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: 2
Extending Resolution by Dynamic Substitution of Boolean Functions 布尔函数的动态替换扩展分辨率
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.145
Saïd Jabbour, J. Lonlac, L. Sais
{"title":"Extending Resolution by Dynamic Substitution of Boolean Functions","authors":"Saïd Jabbour, J. Lonlac, L. Sais","doi":"10.1109/ICTAI.2012.145","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.145","url":null,"abstract":"This paper presents a dynamic substitution technique of Boolean functions. It first recovers a set of Boolean functions from Boolean formula in conjunctive normal form (CNF). Then these functions are used to reduce the size of the learnt clauses by substituting the input arguments by the output ones. Preliminary experiments show the feasibility of our approach on some classes of SAT instances taken from the recent SAT Race and competitions.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125196083","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
Handling Planning Failures with Virtual Actions 使用虚拟操作处理计划失败
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.70
Jicheng Fu, Sijie Tian, Vincent Ng, F. Bastani, I. Yen
{"title":"Handling Planning Failures with Virtual Actions","authors":"Jicheng Fu, Sijie Tian, Vincent Ng, F. Bastani, I. Yen","doi":"10.1109/ICTAI.2012.70","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.70","url":null,"abstract":"Artificial intelligence (AI) planners have been widely used in many fields, such as intelligent agents, autonomous robots, web service compositions, etc. However, existing AI planners share a common problem: When given a problem to solve, they either return a solution if one exists or report that no solution is found. However, simply reporting failure leaves no clues for people to trace the causes of the planning failure. In this paper, we present a novel approach that can propose virtual actions in the event of planning failure. Virtual actions enable traditional planners to succeed and hence return an incomplete plan instead of merely an error message. More importantly, the specifications of the virtual actions suggest what the missing parts may contain, thus providing important clues to users as to the nature of the failure. Experimental results show that our approach constantly returns useful and comprehensible information for humans, thus making AI planning more practical when solving real-world problems.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125229319","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
A New Algorithm for Fuzzy Clustering Able to Find the Optimal Number of Clusters 一种能找到最优聚类数的模糊聚类新算法
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.174
Balkis Abidi, S. Yahia, A. Bouzeghoub
{"title":"A New Algorithm for Fuzzy Clustering Able to Find the Optimal Number of Clusters","authors":"Balkis Abidi, S. Yahia, A. Bouzeghoub","doi":"10.1109/ICTAI.2012.174","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.174","url":null,"abstract":"Tackling, within a classification task, to the problem of inaccuracy explains the development of new theories that offer a formal treatment of imprecise information, especially the theory of fuzzy sets who suggested a new approach taking advantage of the concept of membership function. Nevertheless, clustering algorithms still show limits, particularly for the estimation of the number of clusters. In this paper, through a state of the art of the main fuzzy classification algorithms, we introduce a new algorithm, called Fuzzy-MSOM. The latter aims at palliating to drawback of the determination of the suitable number of clusters in a given data set. Thus, the clustering process is carried out through a multi-level approach. Through the use of fuzzy clustering validity indices, Fuzzy-MSOM overcomes the problem of the estimation of clusters number. The experimental result shows that the proposed clustering technique provides better results compared to the previous algorithms.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127354295","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: 4
Using Relative Classification Probability to Increase Accuracy of Restricted Structure Bayesian Network Classifiers 利用相对分类概率提高限制结构贝叶斯网络分类器的准确率
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.23
Jingsong Wang, M. Valtorta
{"title":"Using Relative Classification Probability to Increase Accuracy of Restricted Structure Bayesian Network Classifiers","authors":"Jingsong Wang, M. Valtorta","doi":"10.1109/ICTAI.2012.23","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.23","url":null,"abstract":"Bayesian networks have been used widely in probabilistic representation and reasoning. Meanwhile, it has been shown that Bayesian classifiers are competitive with many state-of-the-art classifiers. In this paper we present an approach that provides a good tradeoff for the Bayesian network classifier between the number of classified instances and classification accuracy, based on a measure of relative classification probability (RCP). Experiments on benchmark datasets show good support for our hypothesis. The same classifier could reach much higher accuracy over a subset of the original dataset. For most datasets, classification accuracy of the same classifiers can rise high without excluding many instances. The empirical study shows that this idea works well especially for the multiclass classification case.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121851438","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: 2
An Argumentation-Based Approach for Decision Making 基于论证的决策方法
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.82
Jann Müller, A. Hunter
{"title":"An Argumentation-Based Approach for Decision Making","authors":"Jann Müller, A. Hunter","doi":"10.1109/ICTAI.2012.82","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.82","url":null,"abstract":"The formalisation of design decisions serves two purposes: To support the decision maker in choosing which decision to take (decision analysis), and to document the reasons behind decisions for future reference (decision documentation). Approaches which solve the latter task involve a semi-formal pattern of documenting the reasons for and against each of the options, but they generally do not allow an automation of the decision making process. Approaches which solve the former task use a mathematical model of the problem, in which each option is evaluated numerically with respect to some relevant criteria, but they do not support documentation. We investigate the use of argumentation to both analyse and document decisions, solving both tasks with the same method. Additionally, the system we present is able to generate decisions for analysis, instead of relying on a predefined input of options. We collaborated with an aerospace manufacturer to identify common problems in the industry and to create realistic examples from the engineering domain. We show that our system subsumes a certain class of multi criteria decision making problems and that it improves upon previous argumentation-based decision making systems by adding the capability to generate decisions and by clearly defining the semantics used to choose accepted arguments.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"283 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121999192","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: 42
Automatic Discovery and Transfer of MAXQ Hierarchies in a Complex System 复杂系统中MAXQ层次的自动发现与传递
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.165
Hongbing Wang, Wenya Li, Xuan Zhou
{"title":"Automatic Discovery and Transfer of MAXQ Hierarchies in a Complex System","authors":"Hongbing Wang, Wenya Li, Xuan Zhou","doi":"10.1109/ICTAI.2012.165","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.165","url":null,"abstract":"Reinforcement learning has been an important category of machine learning approaches exhibiting self-learning and online learning characteristics. Using reinforcement learning, an agent can learn its behaviors through trial-and-error interactions with a dynamic environment and finally come up with an optimal strategy. Reinforcement learning suffers the curse of dimensionality, though there has been significant progress to overcome this issue in recent years. MAXQ is one of the most common approaches for reinforcement learning. To function properly, MAXQ requires a decomposition of the agent's task into a task hierarchy. Previously, the decomposition can only be done manually. In this paper, we propose a mechanism for automatic subtask discovery. The mechanism applies clustering to automatically construct task hierarchy required by MAXQ, such that MAXQ can be fully automated. We present the design of our mechanism, and demonstrate its effectiveness through theoretical analysis and an extensive experimental evaluation.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129614265","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: 2
Relational Learning with Polynomials 多项式的关系学习
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.163
Ondřej Kuželka, Andrea Szabóová, F. Železný
{"title":"Relational Learning with Polynomials","authors":"Ondřej Kuželka, Andrea Szabóová, F. Železný","doi":"10.1109/ICTAI.2012.163","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.163","url":null,"abstract":"We describe a conceptually simple framework for transformation-based learning in hybrid relational domains. The proposed approach is related to hybrid Markov logic and to Gaussian logic framework. We evaluate the approach in three domains and show that it can achieve state-of-the-art performance while using only limited amount of information.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240997","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
An Algorithm for Finding Robust and Stable Solutions for Constraint Satisfaction Problems with Discrete and Ordered Domains 离散有序域约束满足问题鲁棒稳定解的一种算法
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.122
Laura Climent, R. Wallace, M. Salido, F. Barber
{"title":"An Algorithm for Finding Robust and Stable Solutions for Constraint Satisfaction Problems with Discrete and Ordered Domains","authors":"Laura Climent, R. Wallace, M. Salido, F. Barber","doi":"10.1109/ICTAI.2012.122","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.122","url":null,"abstract":"Many real life problems come from uncertain and dynamic environments, which means that the original problem may change over time. Thus, the solution found for the original problem may become invalid. Dealing with such problems has become an important issue in the field of constraint programming. In some cases, there exists knowledge about the uncertain and dynamic environment. In other cases, this information is unknown or hard to obtain. In this paper, we extend the concept of robustness for Constraint Satisfaction Problems (CSPs) with discrete and ordered domains where the only assumptions made about changes are those inherent in the structure of these problems. We present a search algorithm that searches for both robust and stable solutions for such CSPs. Meeting both criteria simultaneously is a well-known desirable objective for constraint solving in uncertain and dynamic environments.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129365040","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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