An Introduction to MultiAgent Systems.

[서평]「The Unified Modeling Language User Guide」

Evolutionary computation has started to receive significant attention during the last decade, although the origins can be traced back to the late 1950's. This article surveys the history as well as the current state of this rapidly growing field. We describe the purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA) (with links to genetic programming (GP) and classifier systems (CS)), evolution strategies (ES), and evolutionary programming (EP) by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism). Finally, we give a brief overview on the manifold of application domains, although this necessarily must remain incomplete.

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Evolutionary computation: comments on the history and current state

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Hybrid metaheuristics have received considerable interest these recent years in the field of combinatorial optimization. A wide variety of hybrid approaches have been proposed in the literature. In this paper, a taxonomy of hybrid metaheuristics is presented in an attempt to provide a common terminology and classification mechanisms. The taxonomy, while presented in terms of metaheuristics, is also applicable to most types of heuristics and exact optimization algorithms.

As an illustration of the usefulness of the taxonomy an annoted bibliography is given which classifies a large number of hybrid approaches according to the taxonomy.

A Taxonomy of Hybrid Metaheuristics

Direct Chromosome Representation and Advanced Genetic Operators for Production Scheduling

Event-Driven Architecture

Although significant improvements in the development of business applications for mobile devices have been made in recent years, the software development in this area is still not as mature as it is for desktop computers. Therefore, declarative and code generation approaches should be preferred instead of manually coding. In the BAMOS project an architecture has been designed and implemented for the generic and flexible development of mobile applications. The architecture is based on the declarative description of the available services. In this paper we present a model-driven approach for generating almost the complete source code of mobile services. By applying model-driven development within the proposed approach, a new service can be conveniently modeled with a graphical modeling tool and the graphical models are then used to generate the corresponding XML descriptions of the mobile user interface and the workflow specification. In order to use such a service no specific source code has to be implemented on the mobile device.

Model-driven architecture for mobile applications

Event-driven software architecture of decision support systems for M2M is proposed.Complex event processing serves as key technology for intelligent M2M systems.General architecture defines M2M-specific domain, event and state models.Machine data is processed by a CEP event processing pipeline in real-time.It is shown how the architecture can be adapted to real-world M2M scenarios. M2M (machine-to-machine) systems use various communication technologies for automatically monitoring and controlling machines. In M2M systems, each machine emits a continuous stream of data records, which must be analyzed in real-time. Intelligent M2M systems should be able to diagnose their actual states and to trigger appropriate actions as soon as critical situations occur.In this paper, we show how complex event processing (CEP) can be used as the key technology for intelligent M2M systems. We provide an event-driven architecture that is adapted to the M2M domain. In particular, we define different models for the M2M domain, M2M machine states and M2M events. Furthermore, we present a general reference architecture defining the main stages of processing machine data. To prove the usefulness of our approach, we consider two real-world examples 'solar power plants' and 'printers', which show how easily the general architecture can be extended to concrete M2M scenarios.

Intelligent M2M

Production management is crucial for achieving the timely and cost-effective execution of industrial production processes. In recent years, interest has increased in the use of artificial intelligence technologies for production planning and scheduling. However, scheduling research typically has been theoretical, has had a narrow focus, and has not covered adaptation to unforeseen events. The authors' objective has been to use computer-based scheduling systems to enhance the problem-solving capabilities of human domain experts. They have developed a generic framework for building practical scheduling systems. This framework fosters the reuse of algorithms and the integration of knowledge-based technology into the organizational environment. It also supports dynamic adaptation. The authors have used it to implement scheduling systems for dye production, pipeline-fittings production and heart surgery.

Ralf Bruns

Papers

Direct Chromosome Representation and Advanced Genetic Operators for Production Scheduling

Event-Driven Architecture

Model-driven architecture for mobile applications

Intelligent M2M

Knowledge-based scheduling systems in industry and medicine