A Survey of Languages for Specifying Dynamics: A Knowledge Engineering Perspective

A number of formal specification languages for knowledge-based systems has been developed. Characteristics for knowledge-based systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Specification languages for knowledge-based systems have to cover both aspects. They have to provide the means to specify a complex and large amount of knowledge and they have to provide the means to specify the dynamic reasoning behavior of a knowledge-based system. We focus on the second aspect. For this purpose, we survey existing approaches for specifying dynamic behavior in related areas of research. In fact, we have taken approaches for the specification of information systems (Language for Conceptual Modeling and TROLL), approaches for the specification of database updates and logic programming (Transaction Logic and Dynamic Database Logic) and the generic specification framework of abstract state machine

Theories about architecture and performance of multi-agent systems

Multi-agent systems are promising as models of organization because they are based on the idea that most work in human organizations is done based on intelligence, communication, cooperation, and massive parallel processing. They offer an alternative for system theories of organization, which are rather abstract of nature and do not pay attention to the agent level. In contrast, classical organization theories offer a rather rich source of inspiration for developing multi-agent models because of their focus on the agent level. This paper studies the plausibility of theoretical choices in the construction of multi-agent systems. Multi-agent systems have to be plausible from a philosophical, psychological, and organizational point of view. For each of these points of view, alternative theories exist. Philosophically, the organization can be seen from the viewpoints of realism and constructivism. Psychologically, several agent types can be distinguished. A main problem in the construction of psychologically plausible computer agents is the integration of response function systems with representational systems. Organizationally, we study aspects of the architecture of multi-agent systems, namely topology, system function decomposition, coordination and synchronization of agent processes, and distribution of knowledge and language characteristics among agents. For each of these aspects, several theoretical perspectives exist.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design

Cognitive Processes Involved in Solving Information Systems (IS) Design Problems

The author characterizes systems analysis and design as a cognitive problem-solving process and suggests that many implementations fail because Information Systems (IS) designers do not adequately understand the cognitive processes involved. The author explores problem understanding as well as the dynamic relationship between it and plan development and points to areas in which research will not only increase the probability of successful IS implementations but will also contribute to the theoretical foundations of IS