自适应BDI主体研究

该文首先通过对两种智能主体的介绍，分析当前智能主体研究处理非预期情况的两种主要途径，即反应式和慎思式，指出各自存在的问题。进而提出自适应BDI主体的基本框架，在此基础上，论述建立慎思式智能主体适应机制的必要性和可能性。通过引入原子以及公式的相关性，给出意图、目标的一个基于逻辑概念的形式刻画，进而给出“愿望保持性”和“承诺可传递性”的一个近似规范。基于这一规范，可以实现非预期情况下的愿望修正，并支持承诺调整，给出其若干关键问题的形式化结论。     

基于LOBA逻辑的言语行为表示

言语行为是多主体系统中一个有趣而重要的问题.该文从实际推理主体(practical reasoningagents)研究的角度对语用学中的言语行为进行了探讨.在多主体系统中言语行为的研究主要集中在3个方面:1)言语行为的本体描述;2)主体如何推理出合理的言语行为;3)主体如何正确处理其他主体发出的言语行为.这3个方面侧重点不同,但是相互间又紧密关联.重点讨论上述2)和3)两方面的内容,建立了一个主体认知过程的模型,并用可信主体逻辑LOBA(logic of believable agents)进行形式化表示.在主体认知过程的模型中,考虑包括主体的感知、信念、情绪、期望、目标、意图、承诺在内的各种认知成分,通过引入相应的认知动作来考虑这些认知成分之间的动态关系,并在此基础上描述主体如何产生和处理言语行为.在逻辑系统的构建上,LOBA逻辑扩展了KARO逻辑和LORA逻辑,将主体的情绪和认知动作都作为模态算子进行处理,并构建了3层语义模型以解释主体的认知动作.利用上述方法,LOBA可以在更细的粒度上来刻画主体的动态的实际推理过程.     

基于组织结构的多主体协作

基于主体组织的多主体问题求解可以降低问题求解难度和交互复杂性,其中多主体组织的形成规则和多主体的协作与规划是多主体合作的关键。文中提出了一种新的多主体组织模型和一组相关的组织原则,给出了组织规划的方法,提出了多主体组织的形成与消亡形式,并利用扩展的时序逻辑和π演算对上述结论进行了形式化描述,完善了基于组织结构的多主体协作理论,改进了多主体理论研究和多主体编程实践之间脱节的现状。     

认识逻辑(2):多认识主体的认识逻辑MEL

认识逻辑ＥＬ给出了知识和信念在单一认识主体情形下的逻辑框架。本文将认识逻辑ＥＬ推广到多认识主体的情形，得到了一个可靠并且完备的系统ＭＥＬ。ＭＥＬ继承了ＥＬ的全部性质。ＭＥＬ的一个重要特点是各个认识主体的知识是可以共享的。ＭＥＬ可以作为分布式多ａｇｅｎｔ系统的逻辑基础。     

逻辑框架的范畴语义

本文研究逻辑框架的范畴语义，给出逻辑框架模型论中一重要定理－内范涛定理。在此基础上，本文研究逻辑框架编码的语义，给出了可定义性及可编码性定义。     

多主体系统中对其它主体的研究

多主体系统是当前人工智能研究后一个热点，其中，关于知识和动作的推理是一个重要的课题，文中给出了一种知识表示框架，称为ＲＡＯ逻辑，用来对其它主体研究时表示概念和规则，我们从日常推理中抽象出换位原则的规则（ＰＥＰ），ＰＥＰ是ＲＡＯ是的一条公理模式，并且为主体研究其它主体的一个基本规则，它与知识逻辑中的分离规则和（Ｋ）公理具有相似的形式和作用。     

面向社会技术系统的可变承诺自适应实现框架

社会技术系统通常由人类、硬件和软件主体组成,通过它们之间的协同工作满足相关涉众的需求。由于社会技术系统的开放性、动态性和持续变化性,这类系统中的主体需要动态地调整自己的行为,以适应动态变化的环境。一些研究工作已经提出了支持动态重配置和可变承诺的面向社会技术系统的自适应方法。然而,目前还缺少基于这种方法的实现框架。针对这一问题,提出一个基于主体的自适应实现框架,为社会技术系统提供基于可变承诺的自适应能力。该框架是基于JADE(Java Agent Development Framework)平台来实现的,并且提供了面向特定系统的监控器接口和执行器接口来实现个性化配置。最后,通过一个案例分析验证了该实现框架的有效性。     

面向交互的主体能力描述和推理方法研究

主体间的交互对主体能力的影响是主体能力描述和推理需要考虑的一个重要因素．给出了一个面向交互的主体能力描述和推理框架．该框架将描述逻辑中的知识表示结构和任务逻辑中的任务语义结合起来，可以显式地描述主体之间的交互关系对主体能力的影响并可提供可判定的推理服务．建立了一个用于任务可完成性判定的逻辑系统DTL，并证明了它是可靠、完备和可判定的．     

Agent在多Agent系统中计算的意愿理论*

提出了Agent在多Agent系统中计算的意愿理论,以支持Agent计算的理论研究.区分了两种意愿：实现型意愿和维护型意愿.基于多Agent系统计算的逻辑框架,给出了两种意愿新的语义定义,获取和描述了它们的一些重要逻辑属性.     

多Agent合作逻辑中的动作与意图

改进并发博弈结构,给出了一个新模型.消除了不同Agent不准执行相同动作这个与常识不符的假定.给出了5个动作相关函数,使得对Agent、动作与状态三者之间的关系在社会法律约束下的深入考察成为可能.在语法层面同时表述动作和社会法律,提高了多Agent合作逻辑的灵活性和表达能力.在多Agent合作逻辑中引入信念算子和意图算子;考察了两种个体意图和两种群体意图;给出了对命题的个体意图的多子集语义,并把它拓展到对命题的群体意图的语义.     

An environment for reusing ontologies within a knowledge engineering approach

Domain models can be constructed more easily and made more robust by reusing ontologies in a well-defined way. In this paper the KARO approach is introduced which provides various means of retrieving and adapting components of an ontology as part of a domain model construction process. KARO is based on the knowledge-processing component LILOG-KR provided by the LILOG text-understanding system. Above all, the notion of classification is applied for the retrieval of relevant categories. The upper structure of LILOG-KB serves as an exemplary ontology. By integrating KARO into the Model-based and Incremental Knowledge Engineering Environment (MIKE) the reuse of a predefined ontology can be integrated into the development process of expert systems in a systematic way.     

Reasoning about emotional agents

In this article we discuss the role of emotions in artificial agent design, and the use of logic in reasoning about the emotional or affective states an agent can reside in. We do so by extending the KARO framework for reasoning about rational agents appropriately. In particular, we formalize in this framework how emotions are related to the action monitoring capabilities of an agent. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 601–619, 2006.     

Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives

Two distinct and parallel research communities have been working along the lines of the model-based diagnosis approach: the fault detection and isolation (FDI) community and the diagnostic (DX) community that have evolved in the fields of automatic control and artificial intelligence, respectively. This paper clarifies and links the concepts and assumptions that underlie the FDI analytical redundancy approach and the DX consistency-based logical approach. A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.     

SAMPLING QUALITATIVE AND FUZZY VARIABLES AS A TOOL FOR THE GENERAL SYSTEM PROBLEM SOLVER

Abstract

An important phase in the application of the General System Problem Solving framework (GSPS∥ is the choice of the sampling frequency of relevant variables. Optimal sampling frequency is generally a compromise between our endeavour to catch all dynamical changes of a signal without having redundant samples. This problem is not completely solved for crisp metric variables and very little is known about sampling qualitative and fuzzy variables. In this paper, one possible approach based on the data compression is suggested for determining the optimal sampling frequency of ordinal and nominal variables. The submitted approach can be on the specific conditions extended for the fuzzy variables also     

Formal Solution to Systems of Interval Linear or Non-Linear Equations

This is the first of two papers which present the Modal Interval Analysis as a framework where the search and interpretation of formal solutions for a set of simultaneous interval linear or non-linear equations is started on, together with the interval estimations for sets of solutions of real-valued systems in which coefficients and right-hand sides belong to certain intervals. The main purpose of this first paper is to show that the modal intervals are a suitable tool to approach problems where logical reference appear. Thus, it is possible to give a logical meaning to general solutions of the system of equations, obtained, in the linear case, by means of an algorithm whose convergence conditions are studied.     

Pedestrian Travel Behavior Modeling

This paper presents a dynamic mixed discrete-continuous choice approach to modeling pedestrian travel and activity choice behavior in public facilities. The approach views revealed behavior as a manifestation of pedestrians’ preferences by assuming that pedestrians choose the alternative that maximizes expected (subjective) utility, while taking into account the uncertainty in expected traffic conditions. The choice dimensions are trajectories between origin and subsequent destinations, areas where activities are performed (multiple vs. fixed destination), execution of discretionary activities, and finally activities completion times and order.The disutility of a trajectory determines the trajectory choice of the traveler. Destination area choice is included in the modeling by determining time-dependent and destination-specific arrival costs. Furthermore, penalties for not executing a planned activity are introduced into the modeling framework. The resulting modeling approach has a clear analogy with stochastic control theory and dynamic programming in continuous time and space.The main innovations presented here is the relaxation of the assumption that routes are discrete sets of travel links. The approach relaxes the need to build a discrete network, while routes (trajectories) are continuous functions in time and space. At the same time, destination choice is included in the modeling framework.     

Formal compiler construction in a logical framework

The task of designing and implementing a compiler can be a difficult and error-prone process. In this paper, we present a new approach based on the use of higher-order abstract syntax and term rewriting in a logical framework. All program transformations, from parsing to code generation, are cleanly isolated and specified as term rewrites. This has several advantages. The correctness of the compiler depends solely on a small set of rewrite rules that are written in the language of formal mathematics. In addition, the logical framework guarantees the preservation of scoping, and it automates many frequently-occurring tasks including substitution and rewriting strategies. As we show, compiler development in a logical framework can be easier than in a general-purpose language like ML, in part because of automation, and also because the framework provides extensive support for examination, validation, and debugging of the compiler transformations. The paper is organized around a case study, using the MetaPRL logical framework to compile an ML-like language to Intel x86 assembly. We also present a scoped formalization of x86 assembly in which all registers are immutable.     

On the application of multiple criteria decision making to a problem in defence systems acquisition

Multiple criteria decision theory (MCDT) approaches to choice making are receiving increased attention due to the increasing importance society places on incorporating the non-commensurate and conflicting objectives of a situation into the choice making process. Process algorithms for multiple objective optimization theory (MOOT) and multiple attribute utility, theory (MAI5T) motivated a combined approach which utilizes, in an efficient manner, the complementary aspects of both processes. An appropriate application for the multiple criteria approach is a specific military equipment acquisition involving aircraft retrofit. The retrofit of a particular aircraft with equipment designed for a mission which the aircraft was not originally designed to fly typically requires a large systems effort. Specifically, the retrofit of an aircraft with sophisticated electronic warfare (EW) equipment has historically involved inefficiencies and inadequacies including schedule and budgetary overruns and a lack of initially specified final product performance. Development of a useful combined MOOT/MAUT process seems a logical choice to ameliorate the difficulties of current electronic warfare aircraft retrofit design (EWARD) processes. This paper generates a set of criteria for evaluation of alternative retrofit systems in the defence systems acquisition cycle and develops an efficient framework for EWARD through extension of a MCDT approach for this application.     

A comprehensive framework for project selection problem under uncertainty and real-world constraints

This paper proposes a comprehensive framework for project selection problem under uncertainty and subject to real-world constraints, like segmentation, logical, and budget constraints. The framework consists of two main phases. In the first phase, the candidate projects are ranked considering the uncertainty, through a Monte Carlo simulation linked to a multi-criteria approach. In the second phase, the overall complete preorder of the projects in different iterations is first determined and then used in another Monte Carlo simulation linked to an integer programming module in order to effectively drive the final portfolio selection while satisfying the budget, segmentation and other logical constraints. The proposed framework is implemented in a case study to show its usefulness and applicability in practice. Finally, a comparison is carried out between the proposed approach and its deterministic counterpart and the corresponding results are discussed.