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Strategies for contextual reasoning with conflicts in ambient intelligence
Ambient Intelligence environments host various agents that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of such environments and the special characteristics of ambient agents have introduced new research challenges...
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| Published in: | Knowledge and information systems 2011-04, Vol.27 (1), p.45-84 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| cites | cdi_FETCH-LOGICAL-c410t-f21ec56d7edbf0aeda1c2d79a4ff1ede398459745a8d859911bd3d3c30111ac03 |
| container_end_page | 84 |
| container_issue | 1 |
| container_start_page | 45 |
| container_title | Knowledge and information systems |
| container_volume | 27 |
| creator | Bikakis, Antonis Antoniou, Grigoris Hasapis, Panayiotis |
| description | Ambient Intelligence environments host various agents that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of such environments and the special characteristics of ambient agents have introduced new research challenges in the study of Distributed Artificial Intelligence. This paper proposes a solution based on the Multi-Context Systems paradigm, according to which local knowledge of ambient agents is encoded in rule theories (
contexts
), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To resolve potential inconsistencies that may arise from the interaction of contexts through their mappings (
global conflicts
), we use a preference ordering on the system contexts, which may express the confidence that an agent has in the knowledge imported by other agents. On top of this model, we have developed four alternative strategies for
global conflicts
resolution, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts. The four strategies have been respectively implemented in four versions of a distributed algorithm for query evaluation and evaluated in a simulated P2P system. |
| doi_str_mv | 10.1007/s10115-010-0293-0 |
| format | article |
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contexts
), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To resolve potential inconsistencies that may arise from the interaction of contexts through their mappings (
global conflicts
), we use a preference ordering on the system contexts, which may express the confidence that an agent has in the knowledge imported by other agents. On top of this model, we have developed four alternative strategies for
global conflicts
resolution, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts. The four strategies have been respectively implemented in four versions of a distributed algorithm for query evaluation and evaluated in a simulated P2P system.</description><identifier>ISSN: 0219-1377</identifier><identifier>EISSN: 0219-3116</identifier><identifier>DOI: 10.1007/s10115-010-0293-0</identifier><identifier>CODEN: KISNCR</identifier><language>eng</language><publisher>London: Springer-Verlag</publisher><subject>Agents (artificial intelligence) ; Algorithms ; Ambient intelligence ; Applied sciences ; Artificial intelligence ; Cellular telephones ; Classrooms ; Computer Science ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Data Mining and Knowledge Discovery ; Database Management ; Dynamical systems ; Dynamics ; Exact sciences and technology ; Information Storage and Retrieval ; Information Systems and Communication Service ; Information Systems Applications (incl.Internet) ; Intelligent systems ; IT in Business ; Knowledge ; Mapping ; Order disorder ; Preferences ; Regular Paper ; Software ; Strategy ; Studies ; Wireless communications ; Wireless networks</subject><ispartof>Knowledge and information systems, 2011-04, Vol.27 (1), p.45-84</ispartof><rights>Springer-Verlag London Limited 2010</rights><rights>2015 INIST-CNRS</rights><rights>Springer-Verlag London Limited 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c410t-f21ec56d7edbf0aeda1c2d79a4ff1ede398459745a8d859911bd3d3c30111ac03</citedby><cites>FETCH-LOGICAL-c410t-f21ec56d7edbf0aeda1c2d79a4ff1ede398459745a8d859911bd3d3c30111ac03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/858708430/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/858708430?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>315,786,790,11715,27957,27958,36095,36096,44398,75252</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24062297$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Bikakis, Antonis</creatorcontrib><creatorcontrib>Antoniou, Grigoris</creatorcontrib><creatorcontrib>Hasapis, Panayiotis</creatorcontrib><title>Strategies for contextual reasoning with conflicts in ambient intelligence</title><title>Knowledge and information systems</title><addtitle>Knowl Inf Syst</addtitle><description>Ambient Intelligence environments host various agents that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of such environments and the special characteristics of ambient agents have introduced new research challenges in the study of Distributed Artificial Intelligence. This paper proposes a solution based on the Multi-Context Systems paradigm, according to which local knowledge of ambient agents is encoded in rule theories (
contexts
), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To resolve potential inconsistencies that may arise from the interaction of contexts through their mappings (
global conflicts
), we use a preference ordering on the system contexts, which may express the confidence that an agent has in the knowledge imported by other agents. On top of this model, we have developed four alternative strategies for
global conflicts
resolution, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts. The four strategies have been respectively implemented in four versions of a distributed algorithm for query evaluation and evaluated in a simulated P2P system.</description><subject>Agents (artificial intelligence)</subject><subject>Algorithms</subject><subject>Ambient intelligence</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Cellular telephones</subject><subject>Classrooms</subject><subject>Computer Science</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Database Management</subject><subject>Dynamical systems</subject><subject>Dynamics</subject><subject>Exact sciences and technology</subject><subject>Information Storage and Retrieval</subject><subject>Information Systems and Communication Service</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Intelligent systems</subject><subject>IT in Business</subject><subject>Knowledge</subject><subject>Mapping</subject><subject>Order disorder</subject><subject>Preferences</subject><subject>Regular Paper</subject><subject>Software</subject><subject>Strategy</subject><subject>Studies</subject><subject>Wireless communications</subject><subject>Wireless networks</subject><issn>0219-1377</issn><issn>0219-3116</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp9kU1LxDAQhoso-PkDvBVB9FKdaZomPcriJwse1HPIppM10k01yaL-e1t2URD0NAPzzDvv8GbZIcIZAojziIDIC0AooGxYARvZDpTYFAyx3lz3yITYznZjfAFAUSPuZHcPKehEc0cxt33ITe8TfaSl7vJAOvbe-Xn-7tLzOLGdMynmzud6MXPk09Am6jo3J29oP9uyuot0sK572dPV5ePkppjeX99OLqaFqRBSYUskw-tWUDuzoKnVaMpWNLqyFqkl1siKN6LiWraSNw3irGUtM2x4ELUBtpedrHRfQ_-2pJjUwkUz2NCe-mVUUkLNa8nFQJ7-S2ItkEsOEgf06Bf60i-DH_5QkksBsmLjZVxBJvQxBrLqNbiFDp8KQY0xqFUMaohBjTGoced4Layj0Z0N2hsXvxfLCuqybEav5YqLw8jPKfwY-Fv8CyvIlyo</recordid><startdate>20110401</startdate><enddate>20110401</enddate><creator>Bikakis, Antonis</creator><creator>Antoniou, Grigoris</creator><creator>Hasapis, Panayiotis</creator><general>Springer-Verlag</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L.0</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20110401</creationdate><title>Strategies for contextual reasoning with conflicts in ambient intelligence</title><author>Bikakis, Antonis ; Antoniou, Grigoris ; Hasapis, Panayiotis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c410t-f21ec56d7edbf0aeda1c2d79a4ff1ede398459745a8d859911bd3d3c30111ac03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Agents (artificial intelligence)</topic><topic>Algorithms</topic><topic>Ambient intelligence</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Cellular telephones</topic><topic>Classrooms</topic><topic>Computer Science</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Database Management</topic><topic>Dynamical systems</topic><topic>Dynamics</topic><topic>Exact sciences and technology</topic><topic>Information Storage and Retrieval</topic><topic>Information Systems and Communication Service</topic><topic>Information Systems Applications (incl.Internet)</topic><topic>Intelligent systems</topic><topic>IT in Business</topic><topic>Knowledge</topic><topic>Mapping</topic><topic>Order disorder</topic><topic>Preferences</topic><topic>Regular Paper</topic><topic>Software</topic><topic>Strategy</topic><topic>Studies</topic><topic>Wireless communications</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bikakis, Antonis</creatorcontrib><creatorcontrib>Antoniou, Grigoris</creatorcontrib><creatorcontrib>Hasapis, Panayiotis</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI商业信息数据库</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Collection</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Knowledge and information systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bikakis, Antonis</au><au>Antoniou, Grigoris</au><au>Hasapis, Panayiotis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Strategies for contextual reasoning with conflicts in ambient intelligence</atitle><jtitle>Knowledge and information systems</jtitle><stitle>Knowl Inf Syst</stitle><date>2011-04-01</date><risdate>2011</risdate><volume>27</volume><issue>1</issue><spage>45</spage><epage>84</epage><pages>45-84</pages><issn>0219-1377</issn><eissn>0219-3116</eissn><coden>KISNCR</coden><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><notes>ObjectType-Article-2</notes><notes>ObjectType-Feature-1</notes><abstract>Ambient Intelligence environments host various agents that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of such environments and the special characteristics of ambient agents have introduced new research challenges in the study of Distributed Artificial Intelligence. This paper proposes a solution based on the Multi-Context Systems paradigm, according to which local knowledge of ambient agents is encoded in rule theories (
contexts
), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To resolve potential inconsistencies that may arise from the interaction of contexts through their mappings (
global conflicts
), we use a preference ordering on the system contexts, which may express the confidence that an agent has in the knowledge imported by other agents. On top of this model, we have developed four alternative strategies for
global conflicts
resolution, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts. The four strategies have been respectively implemented in four versions of a distributed algorithm for query evaluation and evaluated in a simulated P2P system.</abstract><cop>London</cop><pub>Springer-Verlag</pub><doi>10.1007/s10115-010-0293-0</doi><tpages>40</tpages></addata></record> |
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| ispartof | Knowledge and information systems, 2011-04, Vol.27 (1), p.45-84 |
| issn | 0219-1377 0219-3116 |
| language | eng |
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| subjects | Agents (artificial intelligence) Algorithms Ambient intelligence Applied sciences Artificial intelligence Cellular telephones Classrooms Computer Science Computer science control theory systems Computer systems and distributed systems. User interface Data Mining and Knowledge Discovery Database Management Dynamical systems Dynamics Exact sciences and technology Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) Intelligent systems IT in Business Knowledge Mapping Order disorder Preferences Regular Paper Software Strategy Studies Wireless communications Wireless networks |
| title | Strategies for contextual reasoning with conflicts in ambient intelligence |
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