Expert systems integrated with information systems

Amongst the users of the AIDA applications there is a rapidly growing interest in the use of expert systems, not as independent systems, but as logical extensions of their already existing information systems. In this paper a prototype system (IDEA) will be described that consists of a set of utilities for the construction of an expert system within the context of an AIDA application. Although IDEA does not excel in sophisticated knowledge representations nor in search strategies (the development of which was not our primary concern) it is able to demonstrate that the facilities provided by AIDA together with the IDEA facilities result in an expert system which is characterized by a high degree of integration with the already operational information system.     

Experts' systems instead of expert systems

By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and complexities of their work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems.     

Protected systems in general systems theory

Within the framework of a synergetic theory of protection and protected systems, the concept of a protected system is defined in the context of mainstreams of general systems theory, the relation of such a system to mathematical and computer modeling is shown, and its possible applications are outlined. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 133–141, September–October 2006.     

Generalized control systems,boundary control systems,and delayed control systems

We investigate the relationships between the three classes of systems mentioned in the title: we show that systems with delays in control are a special instance of boundary control systems, and a boundary control system produces a generalized control system when projected onto its (unstable) eigenspaces. We use this observation to investigate the action of feedback on the dynamical behavior of systems with boundary controls. In particular, the well-known fact that spectral controllability is necessary and sufficient for a system with delays in control to be stabilizable is derived from a general rather than from anad hoc method. This paper was written according to the programs of the GNAFA-CNR group, with the financial support of the Italian “Ministero della Pubblica Istruzione.”     

On hybrid systems and closed-loop MPC systems

The following five classes of hybrid systems were recently proven to be equivalent: linear complementarity, extended linear complementarity, mixed logical dynamical systems, piecewise affine systems and max-min-plus-scaling systems. Some of the equivalences were obtained under additional assumptions, such as boundedness of certain system variables. In this paper, for linear or hybrid plants in closed-loop with a model predictive control (MPC) controller based on a linear model fulfilling linear constraints on input and state variables and utilizing a quadratic cost criterion, we provide a simple and direct proof that the closed-loop system is a subclass of any of the former five classes of hybrid systems. This result is of extreme importance, as it opens up the use of tools developed for the mentioned hybrid model classes, such as (robust) stability and safety analysis tools, to study closed-loop properties of MPC     

Numerical systems analysis of multicomponent distributed systems

The paper presents the results in the construction of high-accuracy computational algorithms for the classes of partial derivative problems with discontinuous solutions, including ill-posed and eigenvalue problems. The optimal control in complex distributed systems is investigated. On the basis of the optimal control theory, explicit expressions are obtained for gradients of residual functionals to identify different parameters of multicomponent distributed systems. The possibility of using pseudoinverse matrices to solve some linear inverse problems in a finite number of arithmetic operations is considered.     

Model-driven performance prediction of systems of systems

Systems of systems exhibit characteristics that pose difficulty in modelling and predicting their overall performance capabilities, including the presence of operational independence, emergent behaviour, and evolutionary development. When considering systems of systems within the autonomous defence systems context, these aspects become increasingly critical, as constraints on the performance of the final system are typically driven by hard constraints on space, weight and power. System execution modelling languages and tools permit early prediction of the performance of model-driven systems; however, the focus to date has been on understanding the performance of a model rather than determining whether it meets performance requirements, and only subsequently carrying out analysis to reveal the causes of any requirement violations. Moreover, such an analysis is even more difficult when applied to several systems cooperating to achieve a common goal—a system of systems. In this article, we propose an integrated approach to performance prediction of model-driven real-time embedded defence systems and systems of systems. Our architectural prototyping system supports a scenario-driven experimental platform for evaluating model suitability within a set of deployment and real-time performance constraints. We present an overview of our performance prediction system, demonstrating the integration of modelling, execution and performance analysis, and discuss a case study to illustrate our approach.     

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

The current market's demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature's insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufacturing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.     

Modeling learning technology systems as business systems

The design of Learning Technology Systems, and the Software Systems that support them, is largely conducted on an intuitive, ad hoc basis, thus resulting in inefficient systems that defectively support the learning process. There is now justifiable, increasing effort in formalizing the engineering of Learning Technology Systems in order to achieve better learning effectiveness as well as development efficiency. This paper presents such an approach for designing Learning Technology Systems and their most popular specialization, the Web-based Learning Systems, by modeling them as business systems, using business-modeling methods. The aim is to provide an in-depth analysis and comprehension of the Learning Technology Systems and Web-based Learning Systems domain, that can be used for improving the systems themselves, as well as for building the supporting software systems. Our work is based upon the Learning Technology Systems Architecture standard of IEEE LTSC, on the empirical results of designing Web-based Learning Systems for university courses and on the practices of the Rational Unified Process and the Unified Modeling Language.     

e-Business systems integration: a systems perspective

Systems science has emerged as a meta-discipline and a meta-language, correspondingly, which can be applied to discuss issues in e-business systems and relevant enterprise architecture and enterprise integration. A lot of researches on enterprise architecture and enterprise integration in e-business systems have their theoretical findings and effective practices naturally influenced by systems theory and relative methodologies. This paper strives to review the contribution of systems theory to enterprise architecture and integration. It also tries to summarize methods or tools applied on enterprise systems level, and to investigate many crucial scopes, concepts and their interrelationship in e-business systems integration activities. Finally, this paper presents new prospects in enterprise architecture and integration for e-business systems. All of these may be useful to deal with the increase complex informatics issues of modern enterprises.     

Predictive control,embedded cyberphysical systems and systems of systems – A perspective

Today’s world is changing rapidly due to advancements in information technology, computation and communication. Actuation, communication, sensing, and control are becoming ubiquitous. These technological advancements have led to the widespread availability of information and the possibility to connect systems in unforeseen manner. There is a strong desire for smart(er) cities, buildings, devices, factories, health monitoring – a smarter world. However, designing such a smarter world requires addressing also many challenges resulting from the emerging complex interactions and interoperation of systems. How is it possible to handle the increasing complexity during design and maintenance of such systems? How can one guarantee safety and performance of systems operating over networks which are subject to erroneous communication, delays, and failures of sensors and actuators? Is it possible to design control systems which allow for easy reconfiguration or even self-organization, for example by letting subsystems join and leave larger systems via plug and play strategies? Can one guarantee privacy of the controlled subsystems while exchanging information, which is necessary for maintaining overall system performance? We believe that predictive control is a well suited control approach to tackle some of these challenges due to its flexibility with respect to the formulation of the problem and the possibility to directly take constraints, preview information, as well as models of different complexity of the physical world into account. In this perspective we limit our attention to three areas we believe predictive control methods can provide a basis to tackle the appearing challenges: the efficient and easy implementation of predictive control on omnipresent embedded computation hardware, the question of resource and network aware control, as well as control on the network level of systems of systems. We briefly summarize results from these fields and outline some ideas on challenges, which arise.     

Modeling data-intensive reactive systems with relational transition systems

In this paper, the formalism of Relational Transition Systems (RTSes) is used to model data-intensive reactive systems, and four RTS models of reactive systems based on temporal logic programming, production systems, recurrence equations, and Petri nets are presented. The paper also describes different methods of comparison of the expressive powers of various RTSes in terms of the trajectories they can generate and carries out this comparison for the four RTS formalisms. It is shown that these formalisms have the same expressive power in the deterministic case. The paper also compares expressive powers of non-deterministic production systems and non-deterministic temporal logic programming systems. It is shown that, although the two formalisms are incomparable in the general case, their restricted versions are isomorphic to each other. Received December 7, 1993 / January 26, 1995     

Transaction exchange management systems for successful systems integration

The objective of this paper is to discuss the strategy to be taken by computerized information system managers and developers in the evolving era of computer integrated manufacturing (CIM). Specifically, more concentration should be directed towards a standardized methodology for the management and handling of the transaction data which flows between two or more systems, rathr than upon the hardware and software technology used to “connect” those systems.     

Modeling rule-based systems by stochastic programmed production systems

A new tool, the stochastic programmed production system (SPPS), is proposed for representing rules and control mechanisms in rule-based systems. This approach is based on the stochastic programmed grammars, and its peculiarity is both its well-formalized semantics and its ability to represent most reasoning and control methods used in expert systems today. Since the proposed method is not limited by the particular heuristic organization of the rule-based system it is modeling, the SPPS is more general than existing knowledge-domain-independent expert-system development languages and may help bring a better understanding of the theory of expert systems.     

Transforming linear functional systems into fully integrable systems

A linear (partial) functional system consists of linear partial differential, difference equations or any mixture thereof. We present an algorithm that determines whether linear functional systems are ∂$\partial$-finite, and transforms ∂$\partial$-finite systems to fully integrable ones. The algorithm avoids using Gröbner bases in Laurent–Ore modules when ∂$\partial$-finite systems correspond to finite-dimensional Ore modules.     

PX systems = P systems + X machines

The paper is a survey of the main features of P systems, X machines and of a new computational device called PX system. The sequential and the parallel PX systems are presented. Results reflecting the computational power of these models and their effectiveness in solving NP-complete problems are briefly mentioned.     

The integration of rule systems and database systems

The integration of rule systems into database management systems is explored. Research activities in this area over the past decade are surveyed. The focus is on prototype systems that have been completely specified and the implementation issues encountered. A research agenda which should be addressed by the research community over the next few years is presented     

Generalized-ensemble simulations of spin systems and protein systems

In complex systems such as spin systems and protein systems, conventional simulations in the canonical ensemble will get trapped in states of energy local minima. We employ the generalized-ensemble algorithms in order to overcome this multiple-minima problem. Three well-known generalized-ensemble algorithms, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described. We then present three new generalized-ensemble algorithms based on the combinations of the three methods. Effectiveness of the new methods are tested with a Potts model and protein systems.