@prefix rdf: . @prefix dbpedia: . @prefix opencyc: . dbpedia:Intelligent_agent rdf:type opencyc:Mx4rgQsP1l2xEdif1wACs2IMlQ , opencyc:Mx4rvVitN5wpEbGdrcN5Y29ycA , opencyc:Mx4rvVirnZwpEbGdrcN5Y29ycA , opencyc:Mx4r46fYpnaNEduAAAACs6hbjw . @prefix owl: . @prefix ns4: . dbpedia:Intelligent_agent owl:sameAs ns4:Mx4rvVinb5wpEbGdrcN5Y29ycA , opencyc:Mx4rvVinb5wpEbGdrcN5Y29ycA , . @prefix foaf: . @prefix ns6: . dbpedia:Intelligent_agent foaf:page ns6:Intelligent_agent . @prefix dbpprop: . dbpedia:Intelligent_agent dbpprop:reference , , , . @prefix rdfs: . dbpedia:Intelligent_agent rdfs:label "Intelligent agent"@en , "\u77E5\u7684\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8"@ja , "Agente inteligente (Inteligencia Artificial)"@es , "\u0418\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0439 \u0430\u0433\u0435\u043D\u0442"@ru , "Agente intelligente"@it , "Agentes Inteligentes Artificiais"@pt . @prefix dbpedia-owl: . dbpedia:Intelligent_agent dbpedia-owl:thumbnail ; dbpprop:abstract "In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes and acts upon an environment (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is rational). Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex: a reflex machine such as a thermostat is an intelligent agent, as is a human being, as is a community of human beings working together towards a goal. Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA) to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some definitions of intelligent agents emphasize their, and so prefer the term autonomous intelligent agents. Still others considered goal-directed behavior as the essence of intelligent and so prefer a term borrowed from economics, \"rational agent\". Intelligent agents in artificial intelligence are closely related to agents in economics, and versions of the intelligent agent paradigm are studied in cognitive science, ethics, the philosophy of practical reason, as well as in many interdisciplinary socio-cognitive modeling and computer social simulations. Intelligent agents are also closely related to software agents (an autonomous software program that carries out tasks on behalf of users). In computer science, the term intelligent agent may be used to refer to a software agent that has some intelligence, regardless if it is not a rational agent by Russell and Norvig's definition. For example, autonomous programs used for operator assistance or data mining (sometimes referred to as bots) are also called \"intelligent agents\"."@en , "Un agente inteligente, es una entidad capaz de percibir su entorno, procesar tales percepciones y responder o actuar en su entorno de manera racional, es decir, de manera correcta y tendiendo a maximizar un resultado esperado. En este contexto la racionalidad es la caracter\u00EDstica que posee una elecci\u00F3n de ser correcta, m\u00E1s espec\u00EDficamente, de tender a maximizar un resultado esperado. Este concepto de racionalidad es m\u00E1s general y por ello m\u00E1s adecuado que inteligencia (la cual sugiere entendimiento) para describir el comportamiento de los agentes inteligentes. Por este motivo es mayor el consenso en llamarlos agentes racionales. Un agente inteligente puede ser una entidad f\u00EDsica o virtual. Si bien el t\u00E9rmino agente racional se refiere a agentes artificiales en el campo de la Inteligencia Artificial, tambi\u00E9n puede considerarse agentes racionales a los animales incluido el hombre."@es , "O agente inteligente, \u00E9 aquele que adota a melhor a\u00E7\u00E3o poss\u00EDvel diante de uma situa\u00E7\u00E3o, est\u00E1 presente na resolu\u00E7\u00E3o de uma infinidade de problemas dos usu\u00E1rios comuns. Hoje, a internet conta com diversas iniciativas que utilizam agentes, desde sites que comparam pre\u00E7os de produtos para compra at\u00E9 mecanismos de busca inteligentes, que navegam dentro das p\u00E1ginas web, apresentando o resultado da busca classificado pelo grau de acerto e relev\u00E2ncia dos assuntos. Na l\u00EDngua portuguesa o significado da palavra \"agente\" \u00E9 geralmente interpretada nos dicion\u00E1rios como: Algu\u00E9m que atua; Algu\u00E9m atuando ou fazendo neg\u00F3cios por outro; Procurador, delegado. Estas defini\u00E7\u00F5es atendem algumas caracter\u00EDsticas, mas n\u00E3o contemplam o amplo significado de um agente inteligente. Um agente \u00E9 definido como uma entidade computacional que funciona de forma cont\u00EDnua e aut\u00F4noma em um ambiente restrito, ambiente no qual, podem existir outros agentes com caracter\u00EDsticas comuns ou n\u00E3o. Informalmente um agente \u00E9 algu\u00E9m ou alguma coisa que atua como um procurador com prop\u00F3sito espec\u00EDfico de realizar a\u00E7\u00F5es que podem ser entendidas como ben\u00E9ficas dentro do contexto onde ele atua. Um sistema poder\u00E1 ser visto como um agente se for capaz de perceber seu ambiente por meio de sensores e de agir sobre esse ambiente por interm\u00E9dio de atuadores agregando as caracter\u00EDsticas como autonomia, habilidade social, reatividade e pr\u00F3-atividade. Agentes Reativos Pode desenvolver intelig\u00EAncia a partir de intera\u00E7\u00F5es com seu ambiente, n\u00E3o necessita modelo preestabelecido. S\u00E3o eles Agentes Reativos Simples Respondem a percep\u00E7\u00F5es Interpreta entrada, verifica regra correspondente e age Agentes Reativos baseado em modelo Mat\u00EAm o estado interno pra aspectos n\u00E3o percebido Estado interno modela mundo Pode utilizar percep\u00E7\u00F5es passadas para base em decis\u00F5es Agentes Cognitivos Complexo, com mecanismos de tomada de decis\u00F5es avan\u00E7ados, intera\u00E7\u00F5es sofisticadas e com um objetivo fortemente estabelecido. S\u00E3o eles Agentes baseados em objetivos Procuram atingir alvos Mais flex\u00EDvel que reativos Agentes baseados na utilidade Tentam maximizar suas expectativas Pondera probabilidade de sucesso em rela\u00E7\u00E3o \u00E1 import\u00E2ncia de objetivos"@pt , "\u0412 \u043A\u043E\u043C\u043F\u044C\u044E\u0442\u0435\u0440\u043D\u043E\u0439 \u043D\u0430\u0443\u043A\u0435, \u0438\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0439 \u0430\u0433\u0435\u043D\u0442\u00A0\u2014 \u044D\u0442\u043E \u043F\u0440\u043E\u0433\u0440\u0430\u043C\u043C\u0430, \u0441\u0430\u043C\u043E\u0441\u0442\u043E\u044F\u0442\u0435\u043B\u044C\u043D\u043E \u0432\u044B\u043F\u043E\u043B\u043D\u044F\u044E\u0449\u0430\u044F \u0437\u0430\u0434\u0430\u043D\u0438\u0435, \u0443\u043A\u0430\u0437\u0430\u043D\u043D\u043E\u0435 \u043F\u043E\u043B\u044C\u0437\u043E\u0432\u0430\u0442\u0435\u043B\u0435\u043C \u043A\u043E\u043C\u043F\u044C\u044E\u0442\u0435\u0440\u0430, \u0432 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\u043C\u043E\u0436\u0435\u0442 \u0431\u044B\u0442\u044C \u0440\u0430\u0437\u0440\u0430\u0431\u043E\u0442\u0430\u043D, \u0438\u0441\u043F\u043E\u043B\u044C\u0437\u0443\u044F \u0442\u0440\u0430\u0434\u0438\u0446\u0438\u043E\u043D\u043D\u044B\u0435 \u043C\u0435\u0442\u043E\u0434\u044B \u0440\u0430\u0437\u0440\u0430\u0431\u043E\u0442\u043A\u0438, \u0432 \u043D\u0451\u043C \u043D\u0435\u043C\u043D\u043E\u0433\u0438\u043C \u0431\u043E\u043B\u044C\u0448\u0435 \u0438\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0430, \u0447\u0435\u043C \u0432 \u043F\u043E\u0447\u0442\u043E\u0432\u043E\u043C \u043A\u043B\u0438\u0435\u043D\u0442\u0435 \u0438\u043B\u0438 \u0443\u0442\u0438\u043B\u0438\u0442\u0435 \u0434\u043B\u044F \u0444\u043E\u0440\u043C\u0430\u0442\u0438\u0440\u043E\u0432\u0430\u043D\u0438\u044F \u0436\u0435\u0441\u0442\u043A\u043E\u0433\u043E \u0434\u0438\u0441\u043A\u0430. \u041E\u0434\u043D\u0430\u043A\u043E \u0438\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0439 \u0430\u0433\u0435\u043D\u0442 \u0432\u043E \u0432\u0442\u043E\u0440\u043E\u043C \u0441\u043C\u044B\u0441\u043B\u0435 \u043C\u043E\u0436\u0435\u0442 \u0431\u044B\u0442\u044C \u043F\u043E\u043B\u043D\u043E\u0441\u0442\u044C\u044E \u043D\u0435\u0437\u0430\u0432\u0438\u0441\u0438\u043C\u044B\u043C, \u0432\u044B\u043F\u043E\u043B\u043D\u044F\u044F \u0441\u0432\u043E\u0438 \u0437\u0430\u0434\u0430\u0447\u0438. \u0412 \u043E\u043F\u0435\u0440\u0430\u0446\u0438\u043E\u043D\u043D\u044B\u0445 \u0441\u0438\u0441\u0442\u0435\u043C\u0430\u0445 \u0441\u0435\u043C\u0435\u0439\u0441\u0442\u0432\u0430 UNIX \u0438\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0439 \u0430\u0433\u0435\u043D\u0442, \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u044E\u0449\u0438\u0439 \u0432 \u043F\u0440\u0435\u0434\u0435\u043B\u0430\u0445 \u043E\u0434\u043D\u043E\u0433\u043E \u043A\u043E\u043C\u043F\u044C\u044E\u0442\u0435\u0440\u0430 \u0438\u043B\u0438 \u043B\u043E\u043A\u0430\u043B\u044C\u043D\u043E\u0439 \u0441\u0435\u0442\u0438, \u043E\u0431\u044B\u0447\u043D\u043E \u043D\u0430\u0437\u044B\u0432\u0430\u0435\u0442\u0441\u044F \u0434\u0435\u043C\u043E\u043D\u043E\u043C, \u0432 \u0441\u0435\u043C\u0435\u0439\u0441\u0442\u0432\u0435 Windows\u00A0\u2014 \u0441\u043B\u0443\u0436\u0431\u043E\u0439 (\u0441\u0435\u0440\u0432\u0438\u0441\u043E\u043C). \u041F\u0440\u0438\u043C\u0435\u0440: cron \u0432 UNIX \u0438 \u00AB\u041F\u043B\u0430\u043D\u0438\u0440\u043E\u0432\u0449\u0438\u043A \u0437\u0430\u0434\u0430\u0447\u00BB \u0432 Windows \u0437\u0430\u043D\u0438\u043C\u0430\u044E\u0442\u0441\u044F \u0442\u0435\u043C, \u0447\u0442\u043E \u0437\u0430\u043F\u0443\u0441\u043A\u0430\u044E\u0442 \u0443\u043A\u0430\u0437\u0430\u043D\u043D\u044B\u0435 \u043F\u043E\u043B\u044C\u0437\u043E\u0432\u0430\u0442\u0435\u043B\u0435\u043C \u0437\u0430\u0434\u0430\u043D\u0438\u044F \u0432 \u043E\u043F\u0440\u0435\u0434\u0435\u043B\u0451\u043D\u043D\u044B\u0435 \u043C\u043E\u043C\u0435\u043D\u0442\u044B \u0432\u0440\u0435\u043C\u0435\u043D\u0438."@ru , "\u77E5\u7684\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8\uFF08Intelligent Agent\u3001IA\uFF09\u3068\u306F\u3001\u4E00\u7A2E\u306E\u4EBA\u5DE5\u77E5\u80FD\u7684\u6A5F\u80FD\u3092\u6709\u3059\u308B\u30BD\u30D5\u30C8\u30A6\u30A7\u30A2\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8\u3002\u30E6\u30FC\u30B6\u30FC\u3092\u88DC\u52A9\u3057\u3001\u7E70\u308A\u8FD4\u3057\u884C\u3046\u3079\u304D\u30B3\u30F3\u30D4\u30E5\u30FC\u30BF\u95A2\u9023\u306E\u30BF\u30B9\u30AF\u3092\u30E6\u30FC\u30B6\u30FC\u306B\u4EE3\u308F\u3063\u3066\u884C\u3046\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8\u3067\u3042\u308B\u3002\u901A\u5E38\u306E\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8\u306F\u3001\u56FA\u5B9A\u7684\u306A\u30D7\u30ED\u30B0\u30E9\u30E0\u3055\u308C\u305F\u898F\u5247\u306B\u57FA\u3065\u3044\u3066\u64CD\u4F5C\u8005\u306E\u88DC\u52A9\u3084\u30C7\u30FC\u30BF\u30DE\u30A4\u30CB\u30F3\u30B0\uFF08\u30DC\u30C3\u30C8\u306A\u3069\u3068\u547C\u3070\u308C\u308B\uFF09\u306B\u4F7F\u7528\u3055\u308C\u308B\u306E\u306B\u5BFE\u3057\u3066\u3001\u77E5\u7684\u30A8\u30FC\u30B8\u30A7\u30F3\u30C8\u306F\u5B66\u7FD2\u3057\u300C\u9069\u5FDC\u300D\u3059\u308B\u80FD\u529B\u3092\u6709\u3059\u308B\u3002"@ja , "Per agente si intende una qualunque entit\u00E0 in grado di percepire l'ambiente che lo circonda attraverso dei sensori e di eseguire delle azioni attraverso degli attuatori. Ad esempio, in un essere umano alcuni sensori sono gli occhi e le orecchie. Gli attuatori possono essere le mani, i piedi o pi\u00F9 in generale i muscoli. Nel campo dell'Intelligenza artificiale un obiettivo fondamentale \u00E8 la realizzazione degli agenti intelligenti (o agenti razionali). Nella fattispecie un agente si definisce intelligente se fa la cosa giusta al momento giusto. Per poter stabilire questo occorre fornire una qualche misura delle prestazioni. In particolare \u00E8 importante definire il come e il quando eseguire la valutazione delle azioni. Perci\u00F2 si rende necessario un modello di successo, stabilito a priori, con il quale confrontare i risultati ottenuti. Supponiamo, ad esempio, di avere diversi agenti che risolvono tutti una copia dello stesso puzzle. In questo caso una misura del successo potrebbe essere il numero di pezzi incastrati assieme (definizione del come). Se eseguiamo i test sulle prestazioni dopo pochi minuti, otteniamo risultati migliori per quegli agenti che iniziano veloci. Se per\u00F2 eseguissimo il test dopo un'ora, avremo che magari alcuni agenti, che erano partiti pi\u00F9 lentamente, hanno completato una porzione maggiore del puzzle (definizione del quando). Possiamo quindi definire il comportamento di un agente razionale ideale come quello che: sulla base delle sue percezioni e di eventuali conoscenze predefinite, compie un'azione con lo scopo di massimizzare la misura della prestazioni. Questo include anche il compiere azioni per acquisire informazioni utili (cio\u00E8 acquisire conoscenza). Vediamo ora pi\u00F9 da vicino quella che \u00E8 la struttura di un agente. In generale abbiamo: agente = software + architettura Dove l'architettura \u00E8 solitamente composta dall'hardware che compone l'agente, cio\u00E8 da ci\u00F2 che fisicamente esegue i calcoli. Ad esempio un normale computer o un robot. L' algoritmo \u00E8 il programma che \"guida\" le azioni dell'agente e che viene eseguito dall'architettura. Un modo per definire un agente nel suo complesso, \u00E8 quello di descriverlo in funzione delle sue percezioni, azioni, obiettivi e del suo ambiente. Si parla della cosiddetta descrizione PAGE (Percepts, Actions, Goals, Environment). La descrizione PAGE dell'agente che compone un puzzle potrebbe essere la seguente:"@it ; rdfs:comment "\u0412 \u043A\u043E\u043C\u043F\u044C\u044E\u0442\u0435\u0440\u043D\u043E\u0439 \u043D\u0430\u0443\u043A\u0435, \u0438\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0439 \u0430\u0433\u0435\u043D\u0442\u00A0\u2014 \u044D\u0442\u043E \u043F\u0440\u043E\u0433\u0440\u0430\u043C\u043C\u0430, \u0441\u0430\u043C\u043E\u0441\u0442\u043E\u044F\u0442\u0435\u043B\u044C\u043D\u043E \u0432\u044B\u043F\u043E\u043B\u043D\u044F\u044E\u0449\u0430\u044F \u0437\u0430\u0434\u0430\u043D\u0438\u0435, \u0443\u043A\u0430\u0437\u0430\u043D\u043D\u043E\u0435 \u043F\u043E\u043B\u044C\u0437\u043E\u0432\u0430\u0442\u0435\u043B\u0435\u043C \u043A\u043E\u043C\u043F\u044C\u044E\u0442\u0435\u0440\u0430, \u0432 \u0442\u0435\u0447\u0435\u043D\u0438\u0435 \u0434\u043B\u0438\u0442\u0435\u043B\u044C\u043D\u044B\u0445 \u043F\u0440\u043E\u043C\u0435\u0436\u0443\u0442\u043A\u043E\u0432 \u0432\u0440\u0435\u043C\u0435\u043D\u0438. \u0418\u043D\u0442\u0435\u043B\u043B\u0435\u043A\u0442\u0443\u0430\u043B\u044C\u043D\u044B\u0435 \u0430\u0433\u0435\u043D\u0442\u044B \u0438\u0441\u043F\u043E\u043B\u044C\u0437\u0443\u044E\u0442\u0441\u044F \u0434\u043B\u044F \u0441\u043E\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u044F \u043E\u043F\u0435\u0440\u0430\u0442\u043E\u0440\u0443 \u0438\u043B\u0438 \u0441\u0431\u043E\u0440\u0430 \u0438\u043D\u0444\u043E\u0440\u043C\u0430\u0446\u0438\u0438."@ru , "In artificial intelligence, an intelligent agent (IA) is an autonomous entity which observes and acts upon an environment (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is rational). Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex: a reflex machine such as a thermostat is an intelligent agent, as is a human being, as is a community of human beings working together towards a goal."@en , ""@ja , "Per agente si intende una qualunque entit\u00E0 in grado di percepire l'ambiente che lo circonda attraverso dei sensori e di eseguire delle azioni attraverso degli attuatori. Ad esempio, in un essere umano alcuni sensori sono gli occhi e le orecchie. Gli attuatori possono essere le mani, i piedi o pi\u00F9 in generale i muscoli. Nel campo dell'Intelligenza artificiale un obiettivo fondamentale \u00E8 la realizzazione degli agenti intelligenti (o agenti razionali)."@it , "Un agente inteligente, es una entidad capaz de percibir su entorno, procesar tales percepciones y responder o actuar en su entorno de manera racional, es decir, de manera correcta y tendiendo a maximizar un resultado esperado. En este contexto la racionalidad es la caracter\u00EDstica que posee una elecci\u00F3n de ser correcta, m\u00E1s espec\u00EDficamente, de tender a maximizar un resultado esperado."@es , "O agente inteligente, \u00E9 aquele que adota a melhor a\u00E7\u00E3o poss\u00EDvel diante de uma situa\u00E7\u00E3o, est\u00E1 presente na resolu\u00E7\u00E3o de uma infinidade de problemas dos usu\u00E1rios comuns. Hoje, a internet conta com diversas iniciativas que utilizam agentes, desde sites que comparam pre\u00E7os de produtos para compra at\u00E9 mecanismos de busca inteligentes, que navegam dentro das p\u00E1ginas web, apresentando o resultado da busca classificado pelo grau de acerto e relev\u00E2ncia dos assuntos."@pt ; foaf:depiction . @prefix skos: . @prefix ns11: . dbpedia:Intelligent_agent skos:subject ns11:Artificial_intelligence . @prefix ns12: . dbpedia:Intelligent_agent dbpprop:wikiPageUsesTemplate ns12:harvtxt , ns12:for , ns12:expert-subject , ns12:harvnb ; dbpprop:date "August 2008"@en ; dbpprop:forProperty "intelligent designer"@en , "the term in intelligent design"@en ; dbpprop:p 33 ; dbpprop:loc "chpt. 2"@en ; dbpprop:pp "46-54"@en , "38-44"@en ; dbpprop:harvnbProperty 1998 , "Graesser"@en , 1996 , "Franklin"@en , "Kasobov"@en ; dbpprop:harvtxtProperty 2003 , "Russell"@en , "Norvig"@en . @prefix ns13: . dbpedia:Intelligent_agent dbpprop:hasPhotoCollection ns13:Intelligent_agent . dbpedia:Agent dbpprop:disambiguates dbpedia:Intelligent_agent . dbpedia:FIPA dbpprop:focus dbpedia:Intelligent_agent . dbpedia:Abstract_intelligent_agent dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Autonomous_intelligent_agent dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Intelligent_agents dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Artificial_agent dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Artificial_agents dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Artificial_intelligence_agent dbpprop:redirect dbpedia:Intelligent_agent . dbpedia:Personal_agent dbpprop:redirect dbpedia:Intelligent_agent .