Genetic-algorithm programming environments

This review classifies genetic-algorithm environments into application-oriented systems, algorithm-oriented systems, and toolkits. It also presents detailed case studies of leading environments. Following Holland's (1975) original genetic algorithm proposal, many variations of the basic algorithm have been introduced. However. an important and distinctive feature of all GAs is the population-handling technique. The original GA adopted a generational replacement policy, according to which the whole population is replaced in each generation. Conversely, the steady-state policy used by many subsequent GAs selectively replaces the population. After we introduce GA models and their programming, we present a survey of GA programming environments. We have grouped them into three major classes according to their objectives: application-oriented systems hide the details of GAs and help users develop applications for specific domains; algorithm-oriented systems are based on specific GA models; and toolkits are flexible environments for programming a range of GAs and applications. We review the available environments and describe their common features and requirements. As case studies, we select some specific systems for more detailed examination. To conclude, we discuss likely future developments in GA programming environments     

Volumetric virtual environments

Driven by fast development of both virtual reality and volume visualization,we discuss some critical techniques towards building a volumetric VR system,specifically the modeling,rendering,and manipulations of a volumetric scene.Techniques such as voxel-based object simplification,accelerated volume rendering,fast stereo volume rendering,and volumetric “collision detection“ are introduced and improved,with the idea of demonstrating the possibilities and potential benefits of incorporating volumetric models into VR systems.     

CA-based self-organizing environments

The term Ambient Intelligence (AmI) refers to electronic environments that are sensitive and responsive to the presence of people; in this paper, an example of AmI system whose goal is to enhance the experience of pedestrians moving inside the related physical environment will be presented. The environment is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights). The model for the interaction and action of sensors and actuators is a dissipative multilayered cellular automata, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as the results of simulations of its application in a concrete case study.     

Distributed learning environments

Distributed learning is an instructional model that gives students access to a wide range of resources-teachers, peers, and content such as readings and exercises - independently of place and time. The popularity of distributed learning environments (DLEs) in both professional and academic settings has steadily increased due to 1) the rising demand from traditional students as well as working adults for postsecondary and professional education, 2) advances in information technologies, 3) the Internet's ubiquity, 4) the emergence of high-capacity wire and wireless networks, and 4) the pervasiveness of networked personal computers in both businesses and homes. DLEs must balance with student attributes and instructional strategies. Many universities and colleges, for-profit organizations, and corporate training departments now offer DLE courses and programs. Online distributed learning uses information technologies to provide students with Web-based access to content and resources such as assignments, software simulations, and tests exercises. This approach lets students choose the time, pace, and frequency of their learning activities.     

Domain-oriented design environments

The field of knowledge-based software engineering has been undergoing a shift in emphasis from automatic programming to human augmentation and empowerment. In our research work, we support this shift with an approach that embedshuman-computer cooperative problem-solving tools intodomain-oriented, knowledge-based design environments. Domain orientation reduces the large conceptual distance between problem-domain semantics and software artifacts. Integrated environments support the coevolution of specification and construction while allowing designers to access relevant knowledge at each stage within the software development process.This paper argues thatdomain-oriented design environments (DODEs) are complementary to the approaches pursued withknowledge-based software assistant systems (KBSAs). The DODE extends the KBSA framework by emphasizing a human-centered and domain-oriented approach facilitating communication about evolving systems among all stakeholders. The paper discusses the major challenges for software systems, develops a conceptual framework to address these problems, illustrates DODE with two examples, and assesses the contributions of the KBSA and DODE approaches toward solving these problems.     

Facilitating student-driven constructing of learning environments using Web 2.0 personal learning environments

Web 2.0 Personal Learning Environments (PLEs) are becoming a promising area of development in e-Learning. While enhancing students' control over the entire learning process including constructing learning environment appears to be an essential objective of introducing Web 2.0 PLEs to education, there is little consensus on how to attain this objective. In this paper a theory-informed model to facilitate students' engagement in constructing their learning environment using Web 2.0 PLEs is proposed and evaluated. The model consists of four components: student's control dimensions, student-centric instructional approaches, the learning potential of Web 2.0 tools and services, and technology enhanced learning activities. This model is used to conduct a design-based research in the context of a first grade class in a secondary school in the Netherlands consisting of 29 students (18 girls and 11 boys, aged 11–13 year). The results suggest that the model can facilitate students' engagement in constructing their learning environment through influencing communication between teacher and students, involving students in adding tools, resources, and people into their learning environment, and enhancing their feeling of ownership over their learning environment.     

Designing interactive learning environments

Abstract As computers become more prominent in classroom instruction their modes of use are extending, for example as surrogate teachers in tutoring or as curriculum enrichment in simulation applications where students are more investigative in their learning methods. However, within the classroom such programs often have effects and are used in ways that were not always anticipated by their designers. This argues for computer assisted learning (CAL) environments in which the software is interactive but is able to adapt to different styles of learning and teaching. This paper argues for and describes the design principles of such environments, taking as illustration an application in the fraction domain. Following its implementation, initial evaluation data taken from school-children showed marked performance improvements, and indicated how design features of the system ( FRACTIONLAB ) contributed to their understanding.     

Managing Adaptive Versatile environments

The goal of the MavHome project is to develop technologies to Manage Adaptive Versatile environments. In this paper, we present a complete agent architecture for a single inhabitant intelligent environment and discuss the development, deployment, and techniques utilized in our working intelligent environments. Empirical evaluation of our approach has proven its effectiveness at reducing inhabitant interactions in simulated and real environments.     

Tools for multiple-CPU environments

A brief overview precedes ten separate tool reviews. Five of the tools address the problems of performance analysis, testing, and debugging in a multiple-CPU environment. The first set of tools-Graspin PPSE, and Integral-supports this activity by providing specification or design languages for concurrent applications. The next pair of tools-Pie and Total-supports the development of multiple-CPU software by representing the software's behavior in a parallel or concurrent environment. The next set of five tools is aimed at the problem of serial-to-parallel conversions. The first three tools-E/SP, Mimdizer, and PRETS-recapture the design of the original source code and display it in a graphical form for analysis. The remaining tools-Pat and Aspar-support direct source-to-source transformations. These ten tools are representative of current approaches being taken to address the problem of multiple-CPU computing     

Random environments and automata

In this paper, we propose a machine like a stochastic automaton as the generalized random environment and show that every random environment discussed up to the present is a special case of this machine. The system consisting of this environment and an automaton is equivalent to an autonomous stochastic automaton. Moreover, we introduce some examples for this system.     

Radiosity for dynamic environments

In this paper we present a radiosity algorithm for dynamic scenes with a high level of frame-to-frame coherence. The algorithm is restricted to dynamic environments, where the object's movement is known a priori and the viewpoint is static. Each image is computed as the sum of two images: the base-level image, computed in a pre-process, and the frame-level image computed incrementally at each frame. The computation of the images is based on an importance-driven heuristic approach. The results of the implementation are analysed and discussed. © 1997 John Wiley & Sons, Ltd.     

Composing domain-specific design environments

Domain-specific integrated development environments can help capture specifications in the form of domain models. These tools support the design process by automating analysis and simulating essential system behavior. In addition, they can automatically generate, configure, and integrate target application components. The high cost of developing domain-specific, integrated modeling, analysis, and application-generation environments prevents their penetration into narrower engineering fields that have limited user bases. Model-integrated computing (MIC), an approach to model-based engineering that helps compose domain-specific design environments rapidly and cost effectively, is particularly relevant for specialized computer-based systems domains-perhaps even single projects. The authors describe how MIC provides a way to compose such environments cost effectively and rapidly by using a metalevel architecture to specify the domain-specific modeling language and integrity constraints. They also discuss the toolset that implements MIC and describe a practical application in which using the technology in a tool environment for the process industry led to significant reductions in development and maintenance costs     

Robots in radioactive environments

With improving technology and the growing perception of the need to keep human workers away from high radiation areas, more competitive robotic systems are increasingly becoming available. This article describes our ten years of experience in developing telerobotic systems for maintenance operations in the Spanish nuclear industry. It also describes a teleoperation platform that can be used with standard robots or with specially designed service robots. The modular architecture of this teleoperation platform has allowed the reuse of software components designed for very different applications and drastically reduce development lead time.     

Towards video-based immersive environments

Video provides a comprehensive visual record of environment activity over time. Thus, video data is an attractive source of information for the creation of virtual worlds which require some real-world fidelity. This paper describes the use of multiple streams of video data for the creation of immersive virtual environments. We outline our multiple perspective interactive video (MPI-Video) architecture which provides the infrastructure for the processing and analysis of multiple streams of video data. Our MPI-Video system performs automated analysis of the raw video and constructs a model of the environment and object activity within this environment. This model provides a comprehensive representation of the world monitored by the cameras which, in turn, can be used in the construction of a virtual world. In addition, using the information produced and maintained by the MPI-Video system, our immersive video system generates virtual video sequences. These are sequences of the dynamic environment from an arbitrary view point generated using the real camera data. Such sequences allow a user to navigate through the environment and provide a sense of immersion in the scene. We discuss results from our MPI-Video prototype, outline algorithms for the construction of virtual views and provide examples of a variety of such immersive video sequences.