IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics最新文献_第7页

Neural network output feedback control of robot formations. 机器人编队的神经网络输出反馈控制。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-04-01 Epub Date: 2009-08-04 DOI: 10.1109/TSMCB.2009.2025508

Travis Dierks, Sarangapani Jagannathan

引用次数: 96

Active learning of plans for safety and reachability goals with partial observability. 主动学习具有部分可观察性的安全和可达性目标计划。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-04-01 Epub Date: 2009-08-04 DOI: 10.1109/TSMCB.2009.2025657

Wonhong Nam, Rajeev Alur

{"title":"Active learning of plans for safety and reachability goals with partial observability.","authors":"Wonhong Nam, Rajeev Alur","doi":"10.1109/TSMCB.2009.2025657","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2025657","url":null,"abstract":"Traditional planning assumes reachability goals and/or full observability. In this paper, we propose a novel solution for safety and reachability planning with partial observability. Given a planning domain, a safety property, and a reachability goal, we automatically learn a safe permissive plan to guide the planning domain so that the safety property is not violated and that can force the planning domain to eventually reach states that satisfy the reachability goal, regardless of how the planning domain behaves. Our technique is based on the active learning of regular languages and symbolic model checking. The planning method first learns a safe plan using the L (*) algorithm, which is an efficient active learning algorithm for regular languages. We then check whether the safe plan learned is also permissive by Alternating-time Temporal Logic (ATL) model checking. If the plan is permissive, it is indeed a safe permissive plan. Otherwise, we identify and add a safe string to converge a safe permissive plan. We describe an implementation of the proposed technique and demonstrate that our tool can efficiently construct safe permissive plans for four sets of examples.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"412-20"},"PeriodicalIF":0.0,"publicationDate":"2010-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2025657","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40017526","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

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment. 基于特征结构分配线性二次型调节器设计的状态空间控制器的神经遗传综合。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-04-01 Epub Date: 2009-08-04 DOI: 10.1109/TSMCB.2009.2013722

João Viana da Fonseca Neto, Ivanildo Silva Abreu, Fábio Nogueira da Silva

引用次数: 34

Improving POMDP tractability via belief compression and clustering. 通过信念压缩和聚类提高POMDP的可追溯性。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-31 DOI: 10.1109/TSMCB.2009.2021573

Xin Li, William K Cheung, Jiming Liu

{"title":"Improving POMDP tractability via belief compression and clustering.","authors":"Xin Li, William K Cheung, Jiming Liu","doi":"10.1109/TSMCB.2009.2021573","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2021573","url":null,"abstract":"Partially observable Markov decision process (POMDP) is a commonly adopted mathematical framework for solving planning problems in stochastic environments. However, computing the optimal policy of POMDP for large-scale problems is known to be intractable, where the high dimensionality of the underlying belief space is one of the major causes. In this paper, we propose a hybrid approach that integrates two different approaches for reducing the dimensionality of the belief space: 1) belief compression and 2) value-directed compression. In particular, a novel orthogonal nonnegative matrix factorization is derived for the belief compression, which is then integrated in a value-directed framework for computing the policy. In addition, with the conjecture that a properly partitioned belief space can have its per-cluster intrinsic dimension further reduced, we propose to apply a k-means-like clustering technique to partition the belief space to form a set of sub-POMDPs before applying the dimension reduction techniques to each of them. We have evaluated the proposed belief compression and clustering approaches based on a set of benchmark problems and demonstrated their effectiveness in reducing the cost for computing policies, with the quality of the policies being retained.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"125-36"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2021573","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40009087","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: 17

New delay-dependent exponential H(infinity) synchronization for uncertain neural networks with mixed time delays. 混合时滞不确定神经网络的新时滞相关指数H(∞)同步。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-28 DOI: 10.1109/TSMCB.2009.2024408

Hamid Reza Karimi, Huijun Gao

引用次数: 393

Generalized discriminant analysis: a matrix exponential approach. 广义判别分析:矩阵指数方法。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-31 DOI: 10.1109/TSMCB.2009.2024759

Taiping Zhang, Bin Fang, Yuan Yan Tang, Zhaowei Shang, Bin Xu

{"title":"Generalized discriminant analysis: a matrix exponential approach.","authors":"Taiping Zhang, Bin Fang, Yuan Yan Tang, Zhaowei Shang, Bin Xu","doi":"10.1109/TSMCB.2009.2024759","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2024759","url":null,"abstract":"Linear discriminant analysis (LDA) is well known as a powerful tool for discriminant analysis. In the case of a small training data set, however, it cannot directly be applied to high-dimensional data. This case is the so-called small-sample-size or undersampled problem. In this paper, we propose an exponential discriminant analysis (EDA) technique to overcome the undersampled problem. The advantages of EDA are that, compared with principal component analysis (PCA) + LDA, the EDA method can extract the most discriminant information that was contained in the null space of a within-class scatter matrix, and compared with another LDA extension, i.e., null-space LDA (NLDA), the discriminant information that was contained in the non-null space of the within-class scatter matrix is not discarded. Furthermore, EDA is equivalent to transforming original data into a new space by distance diffusion mapping, and then, LDA is applied in such a new space. As a result of diffusion mapping, the margin between different classes is enlarged, which is helpful in improving classification accuracy. Comparisons of experimental results on different data sets are given with respect to existing LDA extensions, including PCA + LDA, LDA via generalized singular value decomposition, regularized LDA, NLDA, and LDA via QR decomposition, which demonstrate the effectiveness of the proposed EDA method.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"186-97"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2024759","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40009086","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: 164

Adaptive fuzzy switched swing-up and sliding control for the double-pendulum-and-cart system. 双摆小车系统的自适应模糊切换摆动与滑动控制。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-08-04 DOI: 10.1109/TSMCB.2009.2025964

Chin Wang Tao, Jinshiuh Taur, J H Chang, Shun-Feng Su

引用次数: 46

Biomimetic approach to tacit learning based on compound control. 基于复合控制的仿生默会学习方法。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-31 DOI: 10.1109/TSMCB.2009.2014470

Shingo Shimoda, Hidenori Kimura

{"title":"Biomimetic approach to tacit learning based on compound control.","authors":"Shingo Shimoda, Hidenori Kimura","doi":"10.1109/TSMCB.2009.2014470","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2014470","url":null,"abstract":"The remarkable capability of living organisms to adapt to unknown environments is due to learning mechanisms that are totally different from the current artificial machine-learning paradigm. Computational media composed of identical elements that have simple activity rules play a major role in biological control, such as the activities of neurons in brains and the molecular interactions in intracellular control. As a result of integrations of the individual activities of the computational media, new behavioral patterns emerge to adapt to changing environments. We previously implemented this feature of biological controls in a form of machine learning and succeeded to realize bipedal walking without the robot model or trajectory planning. Despite the success of bipedal walking, it was a puzzle as to why the individual activities of the computational media could achieve the global behavior. In this paper, we answer this question by taking a statistical approach that connects the individual activities of computational media to global network behaviors. We show that the individual activities can generate optimized behaviors from a particular global viewpoint, i.e., autonomous rhythm generation and learning of balanced postures, without using global performance indices.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"77-90"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2014470","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40008417","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: 34

A multiagent evolutionary algorithm for combinatorial optimization problems. 组合优化问题的多智能体进化算法。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-28 DOI: 10.1109/TSMCB.2009.2025775

Jing Liu, Weicai Zhong, Licheng Jiao

{"title":"A multiagent evolutionary algorithm for combinatorial optimization problems.","authors":"Jing Liu, Weicai Zhong, Licheng Jiao","doi":"10.1109/TSMCB.2009.2025775","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2025775","url":null,"abstract":"Based on our previous works, multiagent systems and evolutionary algorithms (EAs) are integrated to form a new algorithm for combinatorial optimization problems (CmOPs), namely, MultiAgent EA for CmOPs (MAEA-CmOPs). In MAEA-CmOPs, all agents live in a latticelike environment, with each agent fixed on a lattice point. To increase energies, all agents compete with their neighbors, and they can also increase their own energies by making use of domain knowledge. Theoretical analyses show that MAEA-CmOPs converge to global optimum solutions. Since deceptive problems are the most difficult CmOPs for EAs, in the experiments, various deceptive problems with strong linkage, weak linkage, and overlapping linkage, and more difficult ones, namely, hierarchical problems with treelike structures, are used to validate the performance of MAEA-CmOPs. The results show that MAEA-CmOP outperforms the other algorithms and has a fast convergence rate. MAEA-CmOP is also used to solve large-scale deceptive and hierarchical problems with thousands of dimensions, and the experimental results show that MAEA-CmOP obtains a good performance and has a low computational cost, which the time complexity increases in a polynomial basis with the problem size.","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"229-40"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2025775","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40001691","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: 62

On utilizing association and interaction concepts for enhancing microaggregation in secure statistical databases. 利用关联和交互概念增强安全统计数据库中的微聚合。

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2010-02-01 Epub Date: 2009-07-28 DOI: 10.1109/TSMCB.2009.2024949

B John Oommen, Ebaa Fayyoumi

{"title":"On utilizing association and interaction concepts for enhancing microaggregation in secure statistical databases.","authors":"B John Oommen, Ebaa Fayyoumi","doi":"10.1109/TSMCB.2009.2024949","DOIUrl":"https://doi.org/10.1109/TSMCB.2009.2024949","url":null,"abstract":"This paper presents a possibly pioneering endeavor to tackle the Microaggregation Techniques (MATs) in secure statistical databases by resorting to the principles of associative neural networks (NNs). The prior art has improved the available solutions to the MAT by incorporating proximity information, and this approach is done by recursively reducing the size of the data set by excluding points that are farthest from the centroid and points that are closest to these farthest points. Thus, although the method is extremely effective, arguably, it uses only the proximity information while ignoring the mutual interaction between the records. In this paper, we argue that interrecord relationships can be quantified in terms of the following two entities: 1) their \"association\" and 2) their \"interaction.\" This case means that records that are not necessarily close to each other may still be \"grouped,\" because their mutual interaction, which is quantified by invoking transitive-closure-like operations on the latter entity, could be significant, as suggested by the theoretically sound principles of NNs. By repeatedly invoking the interrecord associations and interactions, the records are grouped into sizes of cardinality \" k,\" where k is the security parameter in the algorithm. Our experimental results, which are done on artificial data and benchmark real-life data sets, demonstrate that the newly proposed method is superior to the state of the art not only based on the Information Loss (IL) perspective but also when it concerns a criterion that involves a combination of the IL and the Disclosure Risk (DR).","PeriodicalId":55006,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics","volume":" ","pages":"198-207"},"PeriodicalIF":0.0,"publicationDate":"2010-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCB.2009.2024949","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40001692","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: 8