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17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)最新文献

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An artificial intelligent approach on longevity modeling 寿命建模的人工智能方法
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.34
Xiaohui Zhang, Shangshang Sun, Mingjiang Zhang
{"title":"An artificial intelligent approach on longevity modeling","authors":"Xiaohui Zhang, Shangshang Sun, Mingjiang Zhang","doi":"10.1109/ICTAI.2005.34","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.34","url":null,"abstract":"Longevity and life science are active topics in biomedicine and other research areas. Because human life is a complex multi-variant natural process, it is complicated yet important to extract expert knowledge that can describe the interactions among different factors and influence of the factors on human life. In this paper, expert knowledge is extracted into a longevity model by using artificial intelligent (AT) techniques: fuzzy logic that reflects prior expert knowledge is used in the preprocessing of bio-medical data; multiple classifier network and decision level data fusion are then applied to improve the modeling accuracy. The test results show that the proposed model is able to identify individuals who belong to longevity group with 93 percent accuracy. This research creates a new approach to explore the cause of human longevity based on comprehensive medical data rather than just from one medical subject. Therefore this methodology accords with the nature of human life more closely","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133039105","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
Towards efficient selection of Web services with reinforcement learning process 利用强化学习过程实现Web服务的高效选择
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.122
Dongjun Cai, Zongwei Luo, Kun Qian, Yang Gao
{"title":"Towards efficient selection of Web services with reinforcement learning process","authors":"Dongjun Cai, Zongwei Luo, Kun Qian, Yang Gao","doi":"10.1109/ICTAI.2005.122","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.122","url":null,"abstract":"As an emerging technology for implementing Web services over the Internet, mobile agent model has several advantages over the traditional RFC model. However, with the popularity of distributed networks (e.g. Internet), Web service providers tend to rely on external resources to complete certain tasks. This definitely increases the difficulty in locating appropriate service providers according to clients' requirements in the new scenario. To address this issue, we propose a reinforcement learning process based on the mobile agent model, which makes agents more efficient and intelligent in selecting Web service providers. Finally, an implementation of our prototype is presented","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131757242","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
Adaptive soft bid determination in bidding strategies for continuous double auctions 连续双拍竞价策略中的自适应软出价确定
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.27
Huiye Ma, Ho-fung Leung
{"title":"Adaptive soft bid determination in bidding strategies for continuous double auctions","authors":"Huiye Ma, Ho-fung Leung","doi":"10.1109/ICTAI.2005.27","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.27","url":null,"abstract":"There are several bidding strategies proposed in the literature for agents in continuous double auctions (CDAs). For most bidding strategies, the asks or bids determined are hard and cannot be compromised. However, for human traders, we notice that the decisions are usually soft and adaptive in different situations. Therefore, we believe that integrating softness and adaptivity into the bidding strategies can enhance the performance of agents. Experimental results confirm that when agents using different bidding strategies make adaptive and soft compromise in various situations, their performance is improved significantly in general. In order to guide agents to adopt soft asks or bids in dynamic and unknown markets, an adaptive mechanism is proposed to adjust the degree of softness of soft asks or bids according to the realtime market context. Experiments results show that agents adopting the adaptive mechanism generally outperform the corresponding agents without the adaptive mechanism","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"11 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130385961","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
Learning optimal values from random walk 从随机游走中学习最优值
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.81
K. Lam, Hong Kong
{"title":"Learning optimal values from random walk","authors":"K. Lam, Hong Kong","doi":"10.1109/ICTAI.2005.81","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.81","url":null,"abstract":"In this paper we extend the random walk example of Sutton and Barto (1998) to a multistage dynamic programming optimization setting with discounted reward. Using Bellman equations on presumed action, the optimal values are derived for general transition probability rho and discount rate gamma, and include the original random walk as a special case. Temporal difference methods with eligibility traces, TD(A), are effective in predicting the optimal values for different rho and gamma; but their performances are found to depend critically on the choice of truncated return in the formulation when gamma is less than 1","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115728014","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
Hybrid genetic algorithm and simulated annealing (HGASA) in global function optimization 全局函数优化中的混合遗传算法和模拟退火算法(HGASA)
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.72
Dingjun Chen, Chung-Yeol Lee, C. Park
{"title":"Hybrid genetic algorithm and simulated annealing (HGASA) in global function optimization","authors":"Dingjun Chen, Chung-Yeol Lee, C. Park","doi":"10.1109/ICTAI.2005.72","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.72","url":null,"abstract":"We have implemented the sequential HGASA on a Sun Workstation machine; its performance seems to be very good in finding the global optimum of a sample function optimization problem as compared with some sequential optimization algorithms that offer low efficiency and limited reliability. However, the sequential HGASA generally needs a long run time cost. So we implemented a parallel HGASA using message passing interface (MPI) on a high performance computer and performed many tests using a set of frequently used function optimization problems. The performance analysis of this parallel approach has been done on IBM Beowulf PCs cluster in terms of program execution time, relative speed up and efficiency","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114803528","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: 19
Applying a Taxonomy of Formation Control in Developing a Robotic System 编队控制分类法在机器人系统开发中的应用
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1142/S0218213007003436
H. Hsu, Alan Liu
{"title":"Applying a Taxonomy of Formation Control in Developing a Robotic System","authors":"H. Hsu, Alan Liu","doi":"10.1142/S0218213007003436","DOIUrl":"https://doi.org/10.1142/S0218213007003436","url":null,"abstract":"Designing cooperative multi-robot systems (MRS) requires expert knowledge both in control and artificial intelligence. Formation control is an important research within the research field of MRS. Since many researchers use different ways in approaching formation control, we try to give a taxonomy in order to help researchers design formation systems in a systematical way. We can analyze formation structures in two categories: control abstraction and robot distinguishability. The control abstraction can be divided into three layers: formation shape, reference type, and robotic control. Furthermore, robots can be classified as anonymous robots or identification robots depending on whether robots are distinguishable according to their inner states. We use this taxonomy to analyze some ground-based formation systems and to state current challenges of formation control. Such information becomes the design know-how in developing a formation system, and a case study of designing a multi-team formation system is introduced to demonstrate the usefulness of the taxonomy","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127066826","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: 10
Adaptive PID control based on RBF neural network identification 基于RBF神经网络辨识的自适应PID控制
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.26
Mingguang Zhang, Xing-gui Wang, Manqiang Liu
{"title":"Adaptive PID control based on RBF neural network identification","authors":"Mingguang Zhang, Xing-gui Wang, Manqiang Liu","doi":"10.1109/ICTAI.2005.26","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.26","url":null,"abstract":"Radial basis function (RBF) neural network (NN) is powerful computational tools that have been used extensively in the areas of pattern recognition, systems modeling and identification. This paper proposes an adaptive PID control method based on RBF neural network identification. This approach can on-line identify the controlled plant with the RBF neural network identifier and the weights of the adaptive PID controller are adjusted timely based-on the identification of the plant and self-learning capability of RBFNN. Simulation result shows that the proposed controller has the adaptability, strong robustness and satisfactory control performance in the nonlinear and time varying system","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124584590","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: 38
Penalty OBS scheme for feedforward neural network 前馈神经网络的惩罚OBS方案
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.93
Jiang Meng
{"title":"Penalty OBS scheme for feedforward neural network","authors":"Jiang Meng","doi":"10.1109/ICTAI.2005.93","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.93","url":null,"abstract":"This paper presented a new scheme called penalty OBS (optimal brain surgeon) for the feedforward neural network learning. The penalty OBS scheme takes OBS pruning case as a penalty item of the network cost function, and develops two applied methods based on the common algorithms of network learning. As a novel revision of OBS, the new scheme not only saves the runtime to calculate Hessian matrix after training, but also improves the generalization a lot and keeps over-linear rapidity of convergence. The simulating results verified the advantages","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130472527","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
Planning with POMDPs using a compact, logic-based representation 使用紧凑的、基于逻辑的表示对pomdp进行规划
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.96
Chenggang Wang, James G. Schmolze
{"title":"Planning with POMDPs using a compact, logic-based representation","authors":"Chenggang Wang, James G. Schmolze","doi":"10.1109/ICTAI.2005.96","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.96","url":null,"abstract":"Partially observable Markov decision processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a convenient and efficient way. Representations built on logic allow for problems to be specified in a compact and transparent manner. Moreover, decision making algorithms can assume and exploit structure found in the state space, actions, observations, and success criteria, and can solve with relative efficiency problems with large state spaces. In recent years researchers have sought to combine the benefits of logic with the expressiveness of POMDPs. In this paper, we show how to build upon and extend the results in this fusing of logic and decision theory. In particular, we present a compact representation of POMDPs and a method to update beliefs after actions and observations. The key contribution is our compact representation of belief states and of the operations used to update them. We then use heuristic search to find optimal plans that maximize expected total reward given an initial belief state","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131771500","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: 16
Accurate active shape model for face alignment 面向面对齐的精确主动形状模型
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.22
Lu Huchuan, Shi Wen-gang
{"title":"Accurate active shape model for face alignment","authors":"Lu Huchuan, Shi Wen-gang","doi":"10.1109/ICTAI.2005.22","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.22","url":null,"abstract":"In this paper, we proposed three improvements on the traditional active shape models, which make the active shape models execute more accurate for face alignment. These improvements including: group method for avoiding to create a distorted shape; best direction and extended width for search profile; enhanced edge profile for special landmark points on the cheek contour of face shape","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123879796","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
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