MAS Ontology: uma ontologia de métodos orientados a agentes

A modelagem orientada a agentes surge como paradigma no desenvolvimento de software, haja vista a quantidade de iniciativas e estudos que remetem à utilização de agentes de software como solução para tratar de problemas mais complexos. Apesar da popularidade de utilização de agentes, especialistas esbarram na falta de universalidade de uma metodologia para construção dos Sistemas Multiagentes (MAS), pois estas acabam pecando pelo excesso ou falta de soluções para modelar o problema. Esta dissertação propõe o uso de uma Ontologia sobre Metodologias Multiagentes, seguindo os princípios da Engenharia de Métodos Situacionais que se propõe a usar fragmentos de métodos para construção de metodologias baseados na especificidade do projeto em desenvolvimento. O objetivo do estudo é sedimentar o conhecimento na área de Metodologias Multiagentes, auxiliando o engenheiro de software a escolher a melhor metodologia ou o melhor fragmento de metodologia capaz de modelar um Sistema Multiagentes.

基于知识的计算机辅助工艺设计系统

介绍了一个较为通用的基于知识的计算机辅助工艺设计（ＣＡＰＰ）系统结构，包括知识表达和关联函数，知识库管理，任务分解与综合策略，解释机制，与其他系统的接口。

数控自动编程专家系统

本文简要地介绍了数控自动编程专家系统.其中包括:专家系统知识表示的形式;分层次的黑板结构;前向推理求解策略和相应的解释功能;系统针对不同类型的曲线组合,采用不同的独立的知识源(KS)进行处理.由于在知识的处理上采用编码技术,在前向推理求解策略中使用启发信息和“剪技”技术,提高了系统的时空效率.系统中的规划程序能自动规划切削路径.输出供数控车床使用的 NC 代码,并可在显示屏上进行图形显示和切削仿真.目前原型系统已经在 IBM-PC 和 Sun3/60计算机上利用FORTRAN 语言实现.

知识表达语言(NFA)及其在石油测井解释专家系统中的应用

石油测井解释是一项逻辑推理和数值计算交错进行的复杂过程。为了描述测井解释专家的这种知识、经验并模拟其思维方式,在扩充纯产生式规则的基础上,我们开发了知识表达语言——NFA,它把逻辑推理和数值计算综合成统一的形式。石油测井解释专家系统 LIX 先后在 INTERDATA-85机和 PE-3230机上实现,现场(胜利油田)运行近两年,解释了130余口井,符合率94%以上。LIX 实质上是 NFA 语言的解释系统,它的研制成功,说明了 NFA 语言的有效性和实用性。

运用神经网络完成汉字句子的格角色分配

According to PDP theory, the author tries to use ANN method in sentence understanding. In input layer, distributed knowledge representation and integrate syntactic, semantic information (of the word in Chinese sentence) and context information are used to complete the case role assignment of six types of Chinese sentence by parallel processing. The model is a four-layer forward network, consisting of input layer, two hidden layers, and output layer(case role layer). In addition, the neural network method and the traditional symbol processing method used in natural language understanding is compared and analyzed, and a conclusion could be made: the neural network should be used as a powerful tool in this area.

Taxonomic Syntax for First-Order Inference

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.

Test Generation Guided Design for Testability

This thesis presents a new approach to building a design for testability (DFT) system. The system takes a digital circuit description, finds out the problems in testing it, and suggests circuit modifications to correct those problems. The key contributions of the thesis research are (1) setting design for testability in the context of test generation (TG), (2) using failures during FG to focus on testability problems, and (3) relating circuit modifications directly to the failures. A natural functionality set is used to represent the maximum functionalities that a component can have. The current implementation has only primitive domain knowledge and needs other work as well. However, armed with the knowledge of TG, it has already demonstrated its ability and produced some interesting results on a simple microprocessor.

Reasoning Modeled as a Society of Communicating Experts

This report describes a domain independent reasoning system. The system uses a frame-based knowledge representation language and various reasoning techniques including constraint propagation, progressive refinement, natural deduction and explicit control of reasoning. A computational architecture based on active objects which operate by exchanging messages is developed and it is shown how this architecture supports reasoning activity. The user interacts with the system by specifying frames and by giving descriptions defining the problem situation. The system uses its reasoning capacity to build up a model of the problem situation from which a solution can interactively be extracted. Examples are discussed from a variety of domains, including electronic circuits, mechanical devices and music. The main thesis is that a reasoning system is best viewed as a parallel system whose control and data are distributed over a large network of processors that interact by exchanging messages. Such a system will be metaphorically described as a society of communicating experts.

Learning and Control in Assistive Robotics for the Elderly

Q. Meng and M. H. Lee, Learning and Control in Assistive Robotics for the Elderly, IEEE Conference on Robotics, Automation and Mechatronics (RAM), Singapore, 2004.

The Epistemological Foundations of Artificial Agents

Lacey, N. J., Lee, M. H. (2003). The Epistemological Foundations of Artificial Agents. Minds and Machines, 13, 339-365.

Towards Fuzzy Compositional Modelling

X. Fu, Q. Shen and R. Zhao. 'Towards fuzzy compositional modelling,' In Proceedings of the 16th International Conference on Fuzzy Systems, 2007, pp. 1233-1238. Sponsorship: EPSRC

Fuzzy rules from ant-inspired computation

M. Galea and Q. Shen. Fuzzy rules from ant-inspired computation. Proceedings of the 13th International Conference on Fuzzy Systems, pages 1691-1696, 2004.

Using a logical model to predict the growth of yeast

Whelan, K. E. and King, R. D. Using a logical model to predict the growth of yeast. BMC Bioinformatics 2008, 9:97

Modelowanie i przetwarzanie wiedzy czaso-przestrzennej. Model XCDC – aspekty teoretyczne oraz rozwiązania aplikacyjne

Wydział Matematyki i Informatyki: Zakład Lingwistyki Informatycznej i Sztucznej Inteligencji