基于动态描述逻辑的多主体协作模型

基于动态描述逻辑的主体模型和协作过程就是既考虑了智能主体的知识表示与推理问题，又紧密地结合主体的设计与编程问题，把表示与推理应用到主体的具体设计中．它充分利用了动态描述逻辑的统一的形式化框架，同时从静态的知识表示与推理和动态的运行与变化两个方面来刻画主体的心智状态和协作过程，探讨了主体信念、行为能力、目标和规划等心智要素的表示、推理与修改以及联合目标的形成、多目标的规划问题．多主体协作模型将理论和实践有机地结合起来，能够充分体现智能主体的本质特征与运行机制，为多主体系统的设计与编程奠定了很好的基础．     

一类扩展的动态描述逻辑

作为描述逻辑的扩展,动态描述逻辑为语义Web服务的建模和推理提供了一种有效途径.在将语义Web服务建模为动作之后,动态描述逻辑从动作执行结果的角度提供了丰富的推理机制,但对于动作的执行过程却不能加以处理.借鉴Pratt关于命题动态逻辑的相关研究,一方面,对动态描述逻辑中动作的语义重新进行定义,将每个动作解释为由关于可能世界的序列组成的集合;另一方面,在动态描述逻辑中引入动作过程断言,用来对动作的执行过程加以刻画.在此基础上提出一类扩展的动态描述逻辑EDDL(X),其中的X表示从ALC(attributive language with complements)到SHOIN(D)等具有不同描述能力的描述逻辑.以X为描述逻辑ALCQO(attributive language with complements,qualified number restrictions and nominals)的情况为例,给出了EDDL(ALCQO)的表判定算法,并证明了算法的可终止性、可靠性和完备性.EDDL(X)可以从动作执行过程和动作执行结果两个方面对动作进行全面的刻画和推理,为语义Web服务的建模和推理提供了进一步的逻辑支持.     

基于动态描述逻辑的主体模型

在动态描述逻辑的基础上，提出了一种智能主体的心智状态模型．它充分利用了动态描述逻辑统一的形式化框架，同时从静态的知识表示与推理和动态的运行与变化两个方面来刻画主体的心智状态．探讨了主体信念、行为能力、目标和规划等心智要素的表示、推理与修改等基本问题．该主体模型将理论和实践有机地结合起来，表达能力强，能够充分体现智能主体的本质特征与运行机制，为智能主体的设计与编程奠定了很好的基础．     

并发行为推理的一种进程代数方法

在人工智能领域，动态系统的行为推理是一个非常热门的研究课题，其中最重要的问题是如何描述系统以及如何进行推理。在这一方面，人们已经提出很多形式化的方法。典型的描述动态系统的方法是引进一个取值随系统进化而改变的“事实”(fact)的集合，以及定义行为对“事实”的影响函数，以方便描述由执行特定的动作引起的状态转移；典型的推理问题是逻辑蕴涵，即寻找一种特定的适合描述动态系统的逻辑，在此逻辑下，系统状态的属性可以由有关系统的一些假设出发推导出来。     

基于动态描述逻辑DDL的动作理论

基于一阶谓词逻辑或高阶逻辑的动作理论与采用命题语言的动作理论之间存在一个关于描述和推理能力的鸿沟;作为描述逻辑的动态扩展,动态描述逻辑DDL为基于描述逻辑的动作刻画和推理提供了一种途径.系统地研究了基于DDL的动作表示和推理问题.首先,在应用描述逻辑对静态领域知识进行刻画的基础上,引入带参数的原子动作定义式和带参数的复...     

动态描述逻辑动作间关系的Petri网分析方法研究

针对动态描述逻辑动作理论在描述和分析多个动作间关系(尤其并发关系)时能力的不足, 提出对多个动态描述逻辑动作间关系描述和分析的 Petri 网方法. 首先讨论了动态描述逻辑动作的等价 Petri 网描述, 进一步通过对动作描述的推理和各个动作的 Petri 网共享合成操作, 得到多个动态描述逻辑动作的 Petri 网系统. 在此基础上, 应用 Petri 网的相关理论与方法, 如可达图分析方法, 研究了多个动态描述逻辑动作间关系的分析与判定方法, 对动态描述逻辑动作理论的描述和分析能力进行了必要的扩充.     

时态认知逻辑CTL＊K的符号化模型检查算法

时序认知逻辑是由时序逻辑和认知逻辑组合而成的逻辑,主要应用于多主体系统的规范定义.大多数时序认知逻辑是基于CTL的,表达能力有限.并且已知的一些模型检查算法存在内存不足和状态爆炸等问题.讨论了基于CTL*的时态认知逻辑cTL*K的语法、语义和模型,它能够在表达力很强的时态逻辑CTL*基础上描述智能体的知识、目标等意向特征.并给出了CTL*K的模型检查算法,其核心思想就是将CTL*K公式的检查问题转化为CTL*公式的模型检查问题,可以使检查的系统规模得以大幅度提高.并且将算法编码后容易集成到NuSMV模型检查器.     

基于动态描述逻辑的语义Web服务推理

语义Web服务的提出是为了解决Web服务资源在语义Web中的自动发现、组合和执行等问题,基本思路是将本体承载的静态知识与对Web服务动态功能的描述有机地结合起来.动态描述逻辑是描述逻辑的一种动态扩展,支持面向语义Web的对动作的描述和推理.文中利用动态描述逻辑DDL(SHOIN(D))的描述和推理功能,提出对语义Web服务进行建模和推理的一种有效途径.从OWL-S中的Process Model出发,将语义Web服务建模为基于DDL(SHOIN(D))的动作理论,其中,对应于Process Model中的原子过程,可以对输入、输出、局部变量、前提条件、结果等多个方面进行建模;对应于Process Model中的复合过程,可以相应地对数据流以及顺序、选择、乱序、条件、迭代、循环等控制结构进行刻画.以建模后得到的动作理论为基础,应用动态描述逻辑的推理机制,可以分别对语义Web服务的可实现性、可执行性、投影、规划等问题进行推理.这些推理功能为语义Web服务的自动发现和自动组合提供了有效的支持.     

Agent-Oriented Probabilistic Logic Programming

Currently, agent-based computing is an active research area, and great efforts have been made towards the agent-oriented programming both from a theoretical and practical view. However, most of them assume that there is no uncertainty in agents＇ mental state and their environment. In other words, under this assumption agent developers are just allowed to specify how his agent acts when the agent is 100% sure about what is true/false. In this paper, this unrealistic assumption is removed and a new agent-oriented probabilistic logic programming language is proposed, which can deal with uncertain information about the world. The programming language is based on a combination of features of probabilistic logic programming and imperative programming.     

Minimal Belief and Negation as Failure in Multi-Agent Systems

We propose an epistemic, nonmonotonic approach to the formalization of knowledge in a multi-agent setting. From the technical viewpoint, a family of nonmonotonic logics, based on Lifschitz's modal logic of minimal belief and negation as failure, is proposed, which allows for formalizing an agent which is able to reason about both its own knowledge and other agents' knowledge and ignorance. We define a reasoning method for such a logic and characterize the computational complexity of the major reasoning tasks in this formalism. From the practical perspective, we argue that our logical framework is well-suited for representing situations in which an agent cooperates in a team, and each agent is able to communicate his knowledge to other agents in the team. In such a case, in many situations the agent needs nonmonotonic abilities, in order to reason about such a situation based on his own knowledge and the other agents' knowledge and ignorance. Finally, we show the effectiveness of our framework in the robotic soccer application domain.     

RAO logic for multiagent framework

In this paper,we deal with how agents reason about knowledge of others in multiagent system.We first present a knowledge representation framework called reasoning about others(RAO) which is designed specifically to represent concepts and rules used in reasoning about knowledge of others.From a class of sentences usually taken by people in daily life to reason about others,a rule called position exchange principle(PEP)is abstracted.PEP is described as an axiom scheme in RAO and regarded as a basic rule for agents to reason about others,and further it has the similar form and role to modus ponens and(K) axion of knowledge logic.The relationship between speech acts and common sense is also discussed which is necessary for RAO.Based on ideas from situation calculus,this relationship is characterized by an axiom schema in RAO.Our theories are also demonstrated by an example.     

Fuzzy trust evaluation and credibility development in multi-agent systems

E-commerce markets can increase their efficiency through the usage of intelligent agents which negotiate and execute contracts on behalf of their owners. The measurement and computation of trust to secure interactions between autonomous agents is crucial for the success of automated e-commerce markets. Building a knowledge sharing network among peer agents helps to overcome trust-related boundaries in an environment where least human intervention is desired. Nevertheless, a risk management model which allows individual customisation to meet the different security needs of agent–owners is vital.The calculation and measurement of trust in unsupervised virtual communities like multi-agent environments involves complex aspects such as credibility rating for opinions delivered by peer agents, or the assessment of past experiences with the peer node one wishes to interact with. The deployment of suitable algorithms and models imitating human reasoning can help to solve these problems.This paper proposes not only a customisable trust evaluation model based on fuzzy logic but also demonstrates the integration of post-interaction processes like business interaction reviews and credibility adjustment. Fuzzy logic provides a natural framework to deal with uncertainty and the tolerance of imprecise data inputs to fuzzy-based systems makes fuzzy reasoning especially attractive for the subjective tasks of trust evaluation, business-interaction review and credibility adjustment.     

Reasoning about reasoning in a meta-level architecture

In this paper we discuss reasoning about reasoning in a multiple agent scenario. We consider agents that are perfect reasoners, loyal, and that can take advantage of both the knowledge and ignorance of other agents. The knowledge representation formalism we use is (full) first order predicate calculus, where different agents are represented by different theories, and reasoning about reasoning is realized via a meta-level representation of knowledge and reasoning. The framework we provide is pretty general: we illustrate it by showing a machine checked solution to the three wisemen puzzle. The agents' knowledge is organized into units: the agent's own knowledge about the world and its knowledge about other agents are units containing object-level knowledge; a unit containing meta-level knowledge embodies the reasoning about reasoning and realizes the link among units. In the paper we illustrate the meta-level architecture we propose for problem solving in a multi-agent scenario; we discuss our approach in relation to the modal one and we compare it with other meta-level architectures based on logic. Finally, we look at a class of applications that can be effectively modeled by exploiting the meta-level approach to reasoning about knowledge and reasoning.     

COMMUNICATION LANGUAGES FOR MULTIAGENT SYSTEMS

Agent Communication Languages (ACLs) have recently acquired a primary role in open multiagent systems, which need a standard communication framework shared by all interacting heterogeneous agents. According to the most important ACL standard proposals so far, agents are supposed to carry out the communication process by performing actions of a specific type, namely, communicative acts, whose semantics is defined in terms of the agents' mental states. Although following the mainstream guidelines inspired by the Speech Act Theory, our work illustrates an alternative model of agent communication, by shifting the focus from agents' mental states to their social state. Taking an existing communicative act library, we provide a semantics for a significant set of acts based on the concept of commitment, and prove that our approach tackles some issues that have not been dealt with in an effective way yet and that may have hindered the rise of an universally accepted ACL standard.     

Quantum Physical Symbol Systems

Because intelligent agents employ physically embodied cognitive systems to reason about the world, their cognitive abilities are constrained by the laws of physics. Scientists have used digital computers to develop and validate theories of physically embodied cognition. Computational theories of intelligence have advanced our understanding of the nature of intelligence and have yielded practically useful systems exhibiting some degree of intelligence. However, the view of cognition as algorithms running on digital computers rests on implicit assumptions about the physical world that are incorrect. Recently, the view is emerging of computing systems as goal-directed agents, evolving during problem solving toward improved world models and better task performance. A full realization of this vision requires a new logic for computing that incorporates learning from experience as an intrinsic part of the logic, and that permits full exploitation of the quantum nature of the physical world. This paper proposes a theory of physically embodied cognitive agents founded upon first-order logic, Bayesian decision theory, and quantum physics. An abstract architecture for a physically embodied cognitive agent is presented. The cognitive aspect is represented as a Bayesian decision theoretic agent; the physical aspect is represented as a quantum process; and these aspects are related through von Neumann’s principle of psycho-physical parallelism. Alternative metaphysical positions regarding the meaning of quantum probabilities and the role of efficacious choices by agents are discussed in relation to the abstract agent architecture. The concepts are illustrated with an extended example from the domain of science fiction.     

A temporal modal defeasible logic for formalizing social commitments in dialogue and argumentation models

In this paper, we extend a temporal defeasible logic with a modal operator Committed to formalize commitments that agents undertake as a consequence of communicative actions (speech acts) during dialogues. We represent commitments as modal sentences. The defeasible dual of the modal operator Committed is a modal operator called Exempted. The logical setting makes the social-commitment based semantics of speech acts verifiable and practical; it is possible to detect if, and when, a commitment is violated and/or complied with. One of the main advantages of the proposed system is that it allows for capturing the nonmonotonic behavior of the commitments induced by the relevant speech acts.