An auction mechanism consists of an allocation rule and a payment rule. There have been several studies on characterizing strategy-proof allocation rules; if the allocation rule satisfies a condition called weak-monotonicity, an appropriate payment rule is guaranteed to exist. One desirable property that an auction mechanism should satisfy is revenue monotonicity; a seller's revenue is guaranteed to weakly increase as the number of bidders grows. In this paper, we first identify a simple condition called summation-monotonicity for characterizing strategy-proof and revenue monotone allocation rules. To the best of our knowledge, this is the first attempt to characterize revenue monotone allocation rules. Based on this characterization, we also examine the connections between revenue monotonicity and false-name-proofness, which means a bidder cannot increase his utility by submitting multiple bids under fictitious names. In a single-item auction, we show that they are basically equivalent; a mechanism is false-name-proof if and only if it is strategy-proof and revenue monotone. On the other hand, we show these two conditions cannot coexist in combinatorial auctions under some minor condition.
{"title":"Characterization of Revenue Monotonicity in Combinatorial Auctions","authors":"Taiki Todo, Atsushi Iwasaki, M. Yokoo","doi":"10.1109/WI-IAT.2010.186","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.186","url":null,"abstract":"An auction mechanism consists of an allocation rule and a payment rule. There have been several studies on characterizing strategy-proof allocation rules; if the allocation rule satisfies a condition called weak-monotonicity, an appropriate payment rule is guaranteed to exist. One desirable property that an auction mechanism should satisfy is revenue monotonicity; a seller's revenue is guaranteed to weakly increase as the number of bidders grows. In this paper, we first identify a simple condition called summation-monotonicity for characterizing strategy-proof and revenue monotone allocation rules. To the best of our knowledge, this is the first attempt to characterize revenue monotone allocation rules. Based on this characterization, we also examine the connections between revenue monotonicity and false-name-proofness, which means a bidder cannot increase his utility by submitting multiple bids under fictitious names. In a single-item auction, we show that they are basically equivalent; a mechanism is false-name-proof if and only if it is strategy-proof and revenue monotone. On the other hand, we show these two conditions cannot coexist in combinatorial auctions under some minor condition.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122658390","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}
Yusuke Takahashi, Daisuke Misugi, Akira Sakatoku, Akihiro Satoh, Akiko Takahashi, K. Sasai, G. Kitagata, Toru Abe, Tetsuo Kinoshita
To reduce the loads imposed on network administrators, we have proposed AIR-NMS, which is a network management support system (NMS) based on Active Information Resource (AIR). In AIR-NMS, various information resources (e.g., state information of a network, practical knowledge of network management) are combined with software agents which have the knowledge and functions for supporting the utilization of the resources, and thus individual resources are given activities as AIRs. Through the organization and cooperation of AIRs, AIR-NMS provides the administrators with practical measures against a wide range of network faults. To make AIR-NMS fit for practical use, this paper proposes a method for achieving the effective installation and utilization of the network management knowledge needed in AIR-NMS.
为了减轻网络管理员的负担，我们提出了一种基于Active Information Resource (Active Information Resource, AIR)的网络管理支持系统AIR-NMS。在AIR-NMS中，各种信息资源(如网络的状态信息、网络管理的实用知识)与具有支持资源利用的知识和功能的软件代理相结合，从而将单个资源作为AIRs赋予活动。AIR-NMS通过AIR-NMS的组织与合作，为管理员提供针对各种网络故障的实用措施。为了使AIR-NMS适应实际应用，本文提出了一种实现AIR-NMS所需的网络管理知识的有效安装和利用的方法。
{"title":"Knowledge Oriented Network Fault Resolution Method Based on Active Information Resource","authors":"Yusuke Takahashi, Daisuke Misugi, Akira Sakatoku, Akihiro Satoh, Akiko Takahashi, K. Sasai, G. Kitagata, Toru Abe, Tetsuo Kinoshita","doi":"10.1109/WI-IAT.2010.123","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.123","url":null,"abstract":"To reduce the loads imposed on network administrators, we have proposed AIR-NMS, which is a network management support system (NMS) based on Active Information Resource (AIR). In AIR-NMS, various information resources (e.g., state information of a network, practical knowledge of network management) are combined with software agents which have the knowledge and functions for supporting the utilization of the resources, and thus individual resources are given activities as AIRs. Through the organization and cooperation of AIRs, AIR-NMS provides the administrators with practical measures against a wide range of network faults. To make AIR-NMS fit for practical use, this paper proposes a method for achieving the effective installation and utilization of the network management knowledge needed in AIR-NMS.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131442316","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}
Qian Zhu, Sashikiran Challa, Prajakta Purohit, Yuyin Sun, M. Lajiness, D. Wild, Ying Ding
Recent years have seen a huge increase in the amount of publicly-available information relevant to drug discovery, including online databases of compound and bioassay information; scholarly publications linking compounds with genes, targets and diseases; and predictive models that can suggest new links between compounds, genes, targets and diseases. However, there is a lack of tools and methods to integrate this information, and in particular to look for pertinent knowledge and relationships across multiple sources. At Indiana University we are tackling this problem by applying aggregative data mining tools and semantic web technologies including using an extensive web service infrastructure, RDF networks and inference engines, ontologies, and automated extraction of information from scholarly literature.
{"title":"Using Web Technologies for Integrative Drug Discovery","authors":"Qian Zhu, Sashikiran Challa, Prajakta Purohit, Yuyin Sun, M. Lajiness, D. Wild, Ying Ding","doi":"10.1109/WI-IAT.2010.45","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.45","url":null,"abstract":"Recent years have seen a huge increase in the amount of publicly-available information relevant to drug discovery, including online databases of compound and bioassay information; scholarly publications linking compounds with genes, targets and diseases; and predictive models that can suggest new links between compounds, genes, targets and diseases. However, there is a lack of tools and methods to integrate this information, and in particular to look for pertinent knowledge and relationships across multiple sources. At Indiana University we are tackling this problem by applying aggregative data mining tools and semantic web technologies including using an extensive web service infrastructure, RDF networks and inference engines, ontologies, and automated extraction of information from scholarly literature.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121879785","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}
In this article we describe the implementation of a diversified investment strategy using 25 intelligent agents. Each agent utilizes several data mining models and other artificial intelligence techniques to autonomously day trade an American stock. The agents were individually tested with out-of-sample data corresponding to the period between February of 2006 and June of 2010, and most achieved an acceptable performance. By integrating the 25 agents in a multi-agent system, we were able to obtain much better results (according to the return and maximum drawdown metrics); this leads us to believe that it might be possible to use one such system in the creation of a profitable hedge fund in which the investment decisions can be made without human intervention.
{"title":"The Agent-Based Hedge Fund","authors":"R. Barbosa, O. Belo","doi":"10.1109/WI-IAT.2010.149","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.149","url":null,"abstract":"In this article we describe the implementation of a diversified investment strategy using 25 intelligent agents. Each agent utilizes several data mining models and other artificial intelligence techniques to autonomously day trade an American stock. The agents were individually tested with out-of-sample data corresponding to the period between February of 2006 and June of 2010, and most achieved an acceptable performance. By integrating the 25 agents in a multi-agent system, we were able to obtain much better results (according to the return and maximum drawdown metrics); this leads us to believe that it might be possible to use one such system in the creation of a profitable hedge fund in which the investment decisions can be made without human intervention.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132695706","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}
The main topic of this paper is description of a proposal of a web shop with user preference searching - PrefShop. A typical web shop was implemented, but new capabilities were added to help the user with finding desired object. Besides preference search, visual hints that clarify the object relevance or the lack of relevance are proposed.
{"title":"Pref Shop A Web Shop with User Preference Search Capabilities","authors":"Branislav Vaclav, A. Eckhardt, P. Vojtás","doi":"10.1109/WI-IAT.2010.295","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.295","url":null,"abstract":"The main topic of this paper is description of a proposal of a web shop with user preference searching - PrefShop. A typical web shop was implemented, but new capabilities were added to help the user with finding desired object. Besides preference search, visual hints that clarify the object relevance or the lack of relevance are proposed.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132183472","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}
Collaborating agents require either prior agreement on the shared vocabularies that they use for communication, or some means of translating between their private ontologies. Thus, techniques that enable agents to build shared vocabularies allow them to share and learn new concepts, and are therefore beneficial when these concepts are required on multiple occasions. However, if this is not carried out in an effective manner then the performance of an agent may be adversely affected by the time required to infer over large augmented ontologies, so causing problems in time-critical scenarios such as search and rescue. In this paper, we present a new technique that enables agents to augment their ontology with carefully selected concepts into their ontology. We contextualise this generic approach in the domain of RoboCup Rescue. Specifically, we show, through empirical evaluation, that our approach saves more civilians, reduces the percentage of the city burnt, and spends the least amount of time accessing its ontology compared with other state of the art benchmark approaches.
{"title":"Collaborative Learning of Ontology Fragments by Co-operating Agents","authors":"Heather S. Packer, Nicholas Gibbins, N. Jennings","doi":"10.1109/WI-IAT.2010.90","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.90","url":null,"abstract":"Collaborating agents require either prior agreement on the shared vocabularies that they use for communication, or some means of translating between their private ontologies. Thus, techniques that enable agents to build shared vocabularies allow them to share and learn new concepts, and are therefore beneficial when these concepts are required on multiple occasions. However, if this is not carried out in an effective manner then the performance of an agent may be adversely affected by the time required to infer over large augmented ontologies, so causing problems in time-critical scenarios such as search and rescue. In this paper, we present a new technique that enables agents to augment their ontology with carefully selected concepts into their ontology. We contextualise this generic approach in the domain of RoboCup Rescue. Specifically, we show, through empirical evaluation, that our approach saves more civilians, reduces the percentage of the city burnt, and spends the least amount of time accessing its ontology compared with other state of the art benchmark approaches.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132294530","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}
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as an instance in an image set, then each image is further viewed as containing instances of local image patches. This representation naturally extends traditional multiple instance learning (MIL) to multi-layers. We then show that, when using the set kernels for all layers, an MMIL problem can be flattened to a simple one-layer MIL. This flattening, when combined with quantized local image patch representation, drastically improves the computational efficiency by two orders. The flattened set kernel is further improved by weighted codewords and an exponential kernel. The proposed approach is applied to a cannabis website classification task, in which we collected a dataset containing more than 220,000 images from 600 websites. In the experiments our approach compares favorably with several state-of-the-art methods.
{"title":"Image Set Classification Using Multi-layer Multiple Instance Learning with Application to Cannabis Website Classification","authors":"Nianhua Xie, Haibin Ling, Weiming Hu","doi":"10.1109/WI-IAT.2010.80","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.80","url":null,"abstract":"We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as an instance in an image set, then each image is further viewed as containing instances of local image patches. This representation naturally extends traditional multiple instance learning (MIL) to multi-layers. We then show that, when using the set kernels for all layers, an MMIL problem can be flattened to a simple one-layer MIL. This flattening, when combined with quantized local image patch representation, drastically improves the computational efficiency by two orders. The flattened set kernel is further improved by weighted codewords and an exponential kernel. The proposed approach is applied to a cannabis website classification task, in which we collected a dataset containing more than 220,000 images from 600 websites. In the experiments our approach compares favorably with several state-of-the-art methods.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134392598","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}
In this paper, we present a Hierarchical Fuzzy Clustering algorithm which uses domain knowledge to automatically determine the number of clusters and their initial values. The algorithm is applied on a collection of web pages and the results are compared with existing algorithms in the literature.
{"title":"Organization of Information for the Web Using Hierarchical Fuzzy Clustering Algorithm Based on Co-occurrence Networks","authors":"Faraz Zaidi, G. Melançon","doi":"10.1109/WI-IAT.2010.86","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.86","url":null,"abstract":"In this paper, we present a Hierarchical Fuzzy Clustering algorithm which uses domain knowledge to automatically determine the number of clusters and their initial values. The algorithm is applied on a collection of web pages and the results are compared with existing algorithms in the literature.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134528577","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}
As wireless sensor network applications grow in complexity, ad-hoc techniques are no longer adequate. Thus, it is crucial that these systems be adaptive and autonomous to remain functional in the face of unreliable communications, dead nodes, and other unexpected failures. We propose to manage sensor networks based on a rigorous multiagent organizational design, which separates application logic from low-level sensor implementation details. The organizational design allows designers to specify high-level goals that the systems will try to achieve based on sensor capabilities.
{"title":"An Organizational Design for Adaptive Sensor Networks","authors":"Walamitien H. Oyenan, S. DeLoach, Gurdip Singh","doi":"10.1109/WI-IAT.2010.32","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.32","url":null,"abstract":"As wireless sensor network applications grow in complexity, ad-hoc techniques are no longer adequate. Thus, it is crucial that these systems be adaptive and autonomous to remain functional in the face of unreliable communications, dead nodes, and other unexpected failures. We propose to manage sensor networks based on a rigorous multiagent organizational design, which separates application logic from low-level sensor implementation details. The organizational design allows designers to specify high-level goals that the systems will try to achieve based on sensor capabilities.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133034884","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}
In this paper a computational model for decision making based on experiences is presented, inspired by the Somatic Marker Hypothesis. The use of the model is illustrated for the domain of fighter pilot decision making. Hereby, simulation runs have been performed upon this scenario, and the results thereof have been formally verified based upon properties inspired on Damasio’s Somatic Marker Hypothesis.
{"title":"An Agent Model for Decision Making Based upon Experiences Applied in the Domain of Fighter Pilots","authors":"M. Hoogendoorn, R. Merk, Jan Treur","doi":"10.1109/WI-IAT.2010.242","DOIUrl":"https://doi.org/10.1109/WI-IAT.2010.242","url":null,"abstract":"In this paper a computational model for decision making based on experiences is presented, inspired by the Somatic Marker Hypothesis. The use of the model is illustrated for the domain of fighter pilot decision making. Hereby, simulation runs have been performed upon this scenario, and the results thereof have been formally verified based upon properties inspired on Damasio’s Somatic Marker Hypothesis.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116995736","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}
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