γ演算到Action演算的转换

Action演算簇(action calculi)作为描述不同并发交互行为的数学框架,可以表示一大类具有某些相同特性的并发形式化模型.试图把(演算(一种基于约束的高阶并发计算模)也包含在action演算簇的框架下.首先定义了一个具体的action演算AC(K_γ),然后给出了从(演算到AC(K_γ)转换的形式描述,最后在定义AC(K_γ)的可观察性、弱互模拟关系和弱等价关系的基础上,以(演算为中间表示,证明了这种转换保持了(演算的弱行为等价性.研究表明,action演算簇可以表示基于约束的并发模型,从而充分说明了action演算簇的描述能力,并且为在action演算簇框架下把(演算与其他并发模型结合并进行比较提供了前提.     

可控网络中多Agent系统信念可达性和收敛速度分析

在可控网络中,利用多agent系统是网络控制的一种重要方法.在可控网络中,多agent系统中所有agent持有的信念必须在决策前达到与网络实际状态一致,即多agent系统的信念应具有可达性,是实现网络合理控制的基础.传统的基于agent行为的信念更新模型建模过程复杂,不适合在网络控制中直接分析多agent系统信念的可达性和收敛速度.基于传统的信念更新模型,提出了信念距离的概念,并在该概念的基础上提出了新的多agent系统信念距离更新模型,并证明了该模型的合理性.该模型对多agent系统信念距离更新过程加以描述,利用线性系统对多agent系统信念收敛过程进行描述,简化了对多agent系统信念可达性和收敛速度分析的复杂性.在该模型基础上,对网络控制中多agent系统信念可达性和收敛速度进行了分析,给出了判断多agent系统信念可达性的充要条件和收敛速度的上限.另外,针对全耦合网络和无标度网络两种复杂网络的特点,分别对两种网络下多agent系统信念可达性和收敛速度进行了讨论.提出的信念距离更新模型具有良好的适应性,为判断多agent系统的信念可达性提供了有力的工具.     

一种意向驱动式面向agent程序设计语言

提出了一种意向驱动式面向agent程序设计语言--AOPLID(agent-oriented programming language with intention driver).该语言基于开放式情景演算OSC(open situation calculus),吸收了GOLOG的合理成分,加入对信念、意向、能力、策略等agent心智成分的处理,使用信念修正原语处理通信交互以及事件响应等外因行动,并采用了一种新颖的离线规划和在线执行相结合的运行方式,从而解决了GOLOG语言在应用于面向agent程序设计时不能有效地描述处理agent心智状态,无法处理外因行动等问题.给出了AOPLID语言语法结构,基于OSC的AOPLID程序语义以及AOPLID程序实例.     

自主Agent结构AASC及其原型支撑系统AASS

介绍了一个能刻画agent的多种特征,尤其是自主性的自主agent结构AASC。此结构结合了BDI结构和情境演算的优点,既能表示agent的信念、目标、策略等心智成分,又能进行行动推理和规划。为了能够方便用户建造自主agent,基于自主agent结构AASC,开发了AASC的原型支撑系统AASS。介绍了AASS的总体结构,讨论了AASS的主要成分类,说明了如何利用该系统开发agent应用系统。     

基于半自治agent的profit-sharing增强学习方法研究

在基于半自治agent的系统中应用profit-sharing增强学习方法,并与基于动态规划的Q-learning 增强学习方法进行比较,在不确定因素较多的动态环境中,当系统状态变化不是一个马尔科夫过程时profit-sharing方法具有很大优势。根据半自治agent中半自治的特性——受制性,提出了一种面向基于半自治agent的增强学习模型,以战场仿真中安全隐蔽的寻找模型为实例对基于半自治agent的profit-sharing增强学习模型进行了试验分析。     

智能Agent程序设计语言IAPL

分析了现有的面向Agent程序设计语言，指出了各自的优缺点。基于智能Agent结构，设计了一个新的智能Agent程序设计语言IAPL；给出了IAPL的语言规范、一组操作原语(信念、意向等心智成份的增加、删除、修改、查询等原语)及Agent之间的通信原语；利用情境演算理论，提供了IAPL语言的语义；提出了在线执行与离线规划相结合的IAPL程序执行方式。     

OSC:一个开放式情景演算系统的研究

在经典情景演算系统的基础上引入了广义信念修正理论，构建了一个开放式情景演算系统OSC(open situation calculus)，克服了经典情景演算系统不能刻画交互通信能力以及对事件的响应处理能力的缺陷．OSC系统保留了经典情景演算系统中的情景流result-of(a，s)，用以刻画行动的影响；同时又引入了新的情景流bel-rev(φ，s)，用以刻画通信交互以及对事件的响应处理等具有开放性信息的活动．OSC系统采用了离线规划与在线执行相结合的运行方式，为面向agent程序设计语言、面向agent智能系统的设计开发等应用提供了有效途径．     

基于关系的两维意向结构

从建构agent角度出发,提出了一个基于关系结构的包括agent意向、信念以及目标等认知状态的框架.在此框架中,实现目标的意向形成了两维序结构,其中一维表示意向间的时序关系,另一维表示意向间的相干关系,在此基础上,研究了信念、意向和目标的相互关系.因为摒弃了传统的用模态算子来刻画agent的意向的方法,所以在构建agent时,可以直接采用意向库以及意向间的时序、相干关系来表示agent的意向,从而缩小了agent理论模型与实际agent结构之间的差异,为agent结构的建立提供了必要的理论基础.     

框架问题的一种可行解

本文提出了一种基于实用原则的框架问题的解决方案,证明该方案的表达能力与Reiter的方案等价,分析了两种方案各自的特色及适用范围,提出了效应公理的完备化概念,给出了效应公理的规则表示形式,这些结果为基于意向驱动的agent模型的建立以及面向agent的程序设计语言AGPLID的提出提供了必要的理论基础.     

AGM信念收缩算子的拓扑式刻画

当agent的信念集是无限集时,传统的基于有限逻辑语言的刻画信念变化(belief change)的简单语义模型通常不再适用。Grdenfors和Makinson 引入的epistemic entrenchment(认知牢固度)模型虽然可以用来从语义上刻画AGM型信念收缩算子,但他们并未给出如何构造一个具体的epistemic entrenchment 的方法。在无限命题逻辑语言的背景下,通过在模型集上引入一个拓扑结构,构造出一种新的用来刻画AGM信念收缩的语义结构,称为认知链,并给出相应表示定理。讨论了epistemic entrenchment与认知链之间的关系。相对epistemic entrenchment而言,认知链具有结构简单并易于构造的特点。     

Agent规范与编程语言SPLAW的语法和语义

本文描述了Ａｇｅｎｔ规范与编程语言ＳＰＬＡＷ的语法，为ＳＰＬＡＷ中的各种语言成分提供了操作语义，并基于标记转换系统给出Ａｇｅｎｔ性质的证明规则。由于ＳＰＬＡＷ的通信部分采用不依赖于具体应用的Ａｇｅｎｔ交互语言ＫＱＭＬ，使遵循同一标准的Ａｇｅｎｔ之间能进行协作问题求解。ＳＰＬＡＷ首次为Ａｇｅｎｔ提供继承支持，使其可以实现具有面向对象特征的多线程系统。ＳＰＬＡＷ屏了为语言引入内部模态词的缺陷，试图从外     

时序Agent程序设计语言TAOPLID的离线解释器

AOPLID是一种面向agent程序设计语言。本文旨在对AOPLID语言进行时序扩充,使之能表达并处理带时间参数的并发行动,基于离线方式下AOPLID程序的语义,用Prolog语言实现时序AOPLID语言(TAOPLID)的离线解释嚣。首先,我们对经典情境演算进行适当改造,使之能描述合时间变元的行动,因为持续行动一般可认为是具有瞬时开始行动和瞬时终止行动的过程,所以可以将一个持续动作分解为两个时间上互不相交的瞬时动作,再引入一个新的关系流刻画这两个瞬时动作的执行情况,从而可在扩充后的情境演算中表达带时间参数的并发行动。其次,为使TAOPLID离线解释嚣方便处理以集合方式表示的TAOPLID程序,设计并实现了TAOPLID预处理嚣,它将TAO—PLID程序的集合形式转换成Prolog子句形式,然后通过TAPOLID离线解释嚣对其解释生成一可执行的原子行动序列。     

2APL: a practical agent programming language

This article presents a BDI-based agent-oriented programming language, called 2APL (A Practical Agent Programming Language). This programming language facilitates the implementation of multi-agent systems consisting of individual agents that may share and access external environments. It realizes an effective integration of declarative and imperative style programming by introducing and integrating declarative beliefs and goals with events and plans. It also provides practical programming constructs to allow the generation, repair, and (different modes of) execution of plans based on beliefs, goals, and events. The formal syntax and semantics of the programming language are given and its relation with existing BDI-based agent-oriented programming languages is discussed.     

Model checking rational agents

Agent-oriented programming techniques seem appropriate for developing systems that operate in complex, dynamic, and unpredictable environments. We aim to address this requirement by developing model-checking techniques for the (automatic or semiautomatic) verification of rational-agent systems written in a logic-based agent-oriented programming language. Typically, developers apply model-checking techniques to abstract models of a system rather than the system implementation. Although this is important for detecting design errors at an early stage, developers might still introduce errors during coding. In contrast, developers can directly apply our model-checking techniques to systems implemented in an agent-oriented programming language, automatically verifying agent systems without the usual gap between design and implementation. We developed our techniques for AgentSpeak, a rational-agent programming language based on the AgentSpeak (L) abstract agent-oriented programming language. AgentSpeak shares many features of the agent-oriented programming paradigm. Similarly, we've developed techniques for automatically translating AgentSpeak programs into the model specification language of existing model-checking systems. In this way, we reduce the problem of verifying that an AgentSpeak system has certain BDI logic properties to a conventional LTL model-checking problem.     

Scheduling in the situation calculus: A case study

We illustrate the utility of the situation calculus for representing complex scheduling tasks by axiomatizing a deadline driven scheduler in the language. The actions arising in such a scheduler are examples of natural actions, as investigated in the concurrent situation calculus by Pinto (PhD thesis, 1994), and later by Reiter (Proc. Common Sense 96, 1996). Because the deadline driven scheduler is sequential, we must first suitably modify Reiter's approach to natural actions so it applies to the sequential case. Having done this, we then show how the situation calculus axiomatization of this scheduler yields a very simple simulator in GOLOG, a situation calculus-based logic programming language for dynamic domains. This revised version was published online in June 2006 with corrections to the Cover Date.     

Agent-oriented model-driven development for JADE with the JADEL programming language

This paper describes, from motivations and main objectives to actual implementation, a novel agent-oriented programming language called JADEL. JADEL is designed to support the effective implementation of JADE agents and multi-agent systems in the scope of real-world model-driven development because it concretely helps developers by natively supporting agent-oriented abstractions, and because it is based on mature industrial-strength technologies. The four core abstractions that JADEL supports, namely agents, behaviours, communication ontologies, and interaction protocols, are presented by gradually introducing the specific syntaxes that the language provides for them. In the last part of the paper, a complete example of a simple JADEL multi-agent system is presented and discussed. Such an example is a well-known example from the official distribution of JADE and many programmers learned the basics of JADE from it. The choice of this example allows comparing JADEL source code with reference Java source code using JADE, and it clearly emphasizes the practical advantages of agent-oriented programming.Section 1 introduces and motivates the presented work. Section 2 surveys major AOP languages and, even if it cannot be considered exhaustive, it highlights the specific features of selected languages that have been relevant for the design of JADEL. Section 3 provides an overview of the features of JADE that are supported by JADEL. Section 4 presents the language in details by discussing main supported abstractions, and by specifying its formal syntax. Section 5 presents the most interesting parts of a complete example of the use of JADEL to develop a simple multi-agent system. Finally, Section 6 concludes the paper with a discussion of the current state of the presented work, and a preliminary assessment of the proposed language.     

Representing Knowledge within the Situation Calculus Using Interval-Valued Epistemic Fluents

The ability of interval arithmetic to provide a finite (and succinct) way to represent uncertainty about a large, possibly uncountable, set of alternatives turns out to be useful in building "intelligent" autonomous agents. In particular, consider the two important issues of reasoning and sensing in intelligent control for autonomous agents. Developing a principled way to combine the two raises complicated issues in knowledge representation. In this paper we describe a solution to the problem. The idea is to incorporate interval arithmetic into the situation calculus. The situation calculus is a well known formalism for describing changing worlds using sorted first-order logic. It can also be used to describe how an agent's knowledge of its world changes. Potentially, this provides a sound basis for incorporating sensing into logic programming. Previous work has relied on a possible worlds approach to knowledge. This leads to an elegant mathematical specification language. Unfortunately, there have been no proposals on how to implement the approach. This is because the number of possible worlds is potentially uncountable. We propose an alternative formalization of knowledge within the situation calculus. Our approach is based on intervals. The advantage is that it is straightforward to implement. Moreover, we can prove that it is sound and (sometimes) complete with respect to the previous possible worlds approach.     

Iterated belief change in the situation calculus

John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.     

Existential rigidity and many modalities in order-sorted logic

Order-sorted logic is a useful tool for knowledge representation and reasoning because it enables representation of sorted terms and formulas along with partially ordered sorts (called sort-hierarchy). However, this logic cannot represent more complex sorted expressions when they are true in any possible world (as rigid) or some possible worlds (as modality) such as time, space, belief, or situation. In this study, we extend order-sorted logic by introducing existential rigidity and many modalities. In the extended logic, sorted modal formulas are interpreted over the Cartesian product of sets of possible worlds. We present a new labeled tableau calculus to check the (un)satisfiability and validity of sorted modal formulas.