{"title":"Meta-agent项目","authors":"Jürgen Dix , V.S. Subrahmanian , George Pick","doi":"10.1016/S0743-1066(99)00062-X","DOIUrl":null,"url":null,"abstract":"<div><p>There are numerous applications where an agent <span><math><mtext>a</mtext></math></span> needs to reason about the beliefs of another agent, as well as about the actions that other agents may take. In [T. Eiter, V.S. Subrahmanian, G. Pick, Heterogeneous Active Agents, I: Semantics, Artificial Intelligence 108(1–2) (1999) 179–255] the concept of an agent program is introduced, and a language within which the operating principles of an agent can be declaratively encoded on top of imperative data structures is defined. In this paper we first introduce certain belief data structures that an agent needs to maintain. Then we introduce the concept of a <em>Meta Agent Program</em> (<span>map</span>), that extends the framework of Refs. [T. Eiter, V.S. Subrahmanian, Heterogeneous Active Agents, II: Algorithms and Complexity, Artificial Intelligence 108(1–2) (1999) 257–307; loc. cit.] so as to allow agents to perform metareasoning. We build a formal semantics for <span>map</span>s, and show how this semantics supports not just beliefs agent <span><math><mtext>a</mtext></math></span> may have about agent <span><math><mtext>b</mtext></math></span> 's state, but also beliefs about agents <span><math><mtext>b</mtext></math></span> 's beliefs about agent <span><math><mtext>c</mtext></math></span> 's actions, beliefs about <span><math><mtext>b</mtext></math></span> 's beliefs about agent <span><math><mtext>c</mtext></math></span> 's state, and so on. Finally, we provide a transansation that takes any <span>map</span> as input and converts it into an agent program such that there is a one–one correspondence between the semantics of the <span>map</span> and the semantics of the resulting agent program. This correspondence allows an implementation of <span>map</span>s to be built on top of an implementation of agent programs.</p></div>","PeriodicalId":101236,"journal":{"name":"The Journal of Logic Programming","volume":"46 1","pages":"Pages 1-60"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0743-1066(99)00062-X","citationCount":"48","resultStr":"{\"title\":\"Meta-agent programs\",\"authors\":\"Jürgen Dix , V.S. Subrahmanian , George Pick\",\"doi\":\"10.1016/S0743-1066(99)00062-X\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There are numerous applications where an agent <span><math><mtext>a</mtext></math></span> needs to reason about the beliefs of another agent, as well as about the actions that other agents may take. In [T. Eiter, V.S. Subrahmanian, G. Pick, Heterogeneous Active Agents, I: Semantics, Artificial Intelligence 108(1–2) (1999) 179–255] the concept of an agent program is introduced, and a language within which the operating principles of an agent can be declaratively encoded on top of imperative data structures is defined. In this paper we first introduce certain belief data structures that an agent needs to maintain. Then we introduce the concept of a <em>Meta Agent Program</em> (<span>map</span>), that extends the framework of Refs. [T. Eiter, V.S. Subrahmanian, Heterogeneous Active Agents, II: Algorithms and Complexity, Artificial Intelligence 108(1–2) (1999) 257–307; loc. cit.] so as to allow agents to perform metareasoning. We build a formal semantics for <span>map</span>s, and show how this semantics supports not just beliefs agent <span><math><mtext>a</mtext></math></span> may have about agent <span><math><mtext>b</mtext></math></span> 's state, but also beliefs about agents <span><math><mtext>b</mtext></math></span> 's beliefs about agent <span><math><mtext>c</mtext></math></span> 's actions, beliefs about <span><math><mtext>b</mtext></math></span> 's beliefs about agent <span><math><mtext>c</mtext></math></span> 's state, and so on. Finally, we provide a transansation that takes any <span>map</span> as input and converts it into an agent program such that there is a one–one correspondence between the semantics of the <span>map</span> and the semantics of the resulting agent program. This correspondence allows an implementation of <span>map</span>s to be built on top of an implementation of agent programs.</p></div>\",\"PeriodicalId\":101236,\"journal\":{\"name\":\"The Journal of Logic Programming\",\"volume\":\"46 1\",\"pages\":\"Pages 1-60\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0743-1066(99)00062-X\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Logic Programming\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S074310669900062X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Logic Programming","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S074310669900062X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 48
摘要
在许多应用程序中,一个代理需要推断另一个代理的信念,以及其他代理可能采取的行动。在[T。Eiter, V.S. Subrahmanian, G. Pick,异构主动代理,I:语义,人工智能108(1-2)(1999)179-255),介绍了代理程序的概念,并定义了一种语言,在这种语言中,代理的操作原则可以在命使式数据结构的基础上进行声明式编码。本文首先介绍了智能体需要维护的信念数据结构。然后,我们引入了元代理程序(map)的概念,扩展了Refs的框架。(T。Eiter, V.S. Subrahmanian,异构主动代理,II:算法和复杂性,人工智能108(1-2)(1999)257-307;疯狂的。以允许代理执行元推理。我们为地图建立了一个形式化语义,并展示了这个语义如何不仅支持代理a对代理b状态的信念,还支持代理b对代理c行为的信念,以及代理b对代理c状态的信念,等等。最后,我们提供了一个转换,它将任何映射作为输入并将其转换为代理程序,以便在映射的语义和生成的代理程序的语义之间存在一对一的对应关系。这种对应关系允许在代理程序的实现之上构建地图的实现。
There are numerous applications where an agent needs to reason about the beliefs of another agent, as well as about the actions that other agents may take. In [T. Eiter, V.S. Subrahmanian, G. Pick, Heterogeneous Active Agents, I: Semantics, Artificial Intelligence 108(1–2) (1999) 179–255] the concept of an agent program is introduced, and a language within which the operating principles of an agent can be declaratively encoded on top of imperative data structures is defined. In this paper we first introduce certain belief data structures that an agent needs to maintain. Then we introduce the concept of a Meta Agent Program (map), that extends the framework of Refs. [T. Eiter, V.S. Subrahmanian, Heterogeneous Active Agents, II: Algorithms and Complexity, Artificial Intelligence 108(1–2) (1999) 257–307; loc. cit.] so as to allow agents to perform metareasoning. We build a formal semantics for maps, and show how this semantics supports not just beliefs agent may have about agent 's state, but also beliefs about agents 's beliefs about agent 's actions, beliefs about 's beliefs about agent 's state, and so on. Finally, we provide a transansation that takes any map as input and converts it into an agent program such that there is a one–one correspondence between the semantics of the map and the semantics of the resulting agent program. This correspondence allows an implementation of maps to be built on top of an implementation of agent programs.