117,268 research outputs found
Biology of Applied Digital Ecosystems
A primary motivation for our research in Digital Ecosystems is the desire to
exploit the self-organising properties of biological ecosystems. Ecosystems are
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties have not been made explicit in Digital Ecosystems research.
Here, we discuss how biological properties contribute to the self-organising
features of biological ecosystems, including population dynamics, evolution, a
complex dynamic environment, and spatial distributions for generating local
interactions. The potential for exploiting these properties in artificial
systems is then considered. We suggest that several key features of biological
ecosystems have not been fully explored in existing digital ecosystems, and
discuss how mimicking these features may assist in developing robust, scalable
self-organising architectures. An example architecture, the Digital Ecosystem,
is considered in detail. The Digital Ecosystem is then measured experimentally
through simulations, with measures originating from theoretical ecology, to
confirm its likeness to a biological ecosystem. Including the responsiveness to
requests for applications from the user base, as a measure of the 'ecological
succession' (development).Comment: 9 pages, 4 figure, conferenc
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
Collaborative trails in e-learning environments
This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas â experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future
Constructing a Virtual Training Laboratory Using Intelligent Agents
This paper reports on the results and experiences of the Trilogy project; a collaborative project concerned with the development of a virtual research laboratory using intelligence agents. This laboratory is designed to support the training of research students in telecommunications traffic engineering. Training research students involves a number of basic activities. They may seek guidance from, or exchange ideas with, more experienced colleagues. High quality academic papers, books and research reports provide a sound basis for developing and maintaining a good understanding of an area of research. Experimental tools enable new ideas to be evaluated, and hypotheses tested. These three components-collaboration, information and experimentation- are central to any research activity, and a good training environment for research should integrate them in a seamless fashion. To this end, we describe the design and implementation of an agent-based virtual laboratory
Recommended from our members
Harnessing agile concepts for the development of intelligent systems
Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims
The Semantic Grid: A future e-Science infrastructure
e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practiceâaspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid
PlanetOnto: from news publishing to integrated knowledge management support
Given a scenario in which members of an academic community collaboratively construct and share an archive of news items, several knowledge management challenges arise. The authors' integrated suite of tools, called PlanetOnto, supports a speedy but high quality publishing process, allows ontology-driven document formalization and augments standard browsing and search facilities with deductive knowledge retrieva
Software Agents
being used, and touted, for applications as diverse as personalised information management, electronic commerce, interface design, computer games, and management of complex commercial and industrial processes. Despite this proliferation, there is, as yet, no commonly agreed upon definition of exactly what an agent is â Smith et al. (1994) define it as âa persistent software entity dedicated to a specific purposeâ; Selker (1994) takes agents to be âcomputer programs that simulate a human relationship by doing something that another person could do for youâ; and Janca (1995) defines an agent as âa software entity to which tasks can be delegatedâ. To capture this variety, a relatively loose notion of an agent as a self-contained program capable of controlling its own decision making and acting, based on its perception of its environment, in pursuit of one or more objectives will be used here. Within the extant applications, three distinct classes of agent can be identified. At the simplest level, there are âgopher â agents, which execute straightforward tasks based on pre-specified rules and assumptions (eg inform me when the share price deviates by 10 % from its mean position or tell me when I need to reorder stock items). The next level of sophistication involves âservice performingâ agents, which execute a well defined task at the request of a user (eg find me the cheapest flight to Paris or arrange a meeting with the managing director some day next week). Finally, there are âpredictive â agents, which volunteer information or services to a user, without being explicitly asked, whenever it is deemed appropriate (eg an agent may monitor newsgroups on the INTERNET and return discussions that it believes to be of interest to the user or a holiday agent may inform its user that a travel firm is offering large discounts on holidays to South Africa knowing that the user is interested in safaris). Common to all these classes are the following key hallmarks of agenthoo
Intelligent Decisional Assistant that Facilitate the Choice of a Proper Computer System Applied in Busines
The choice of a proper computer system is not an easy task for a decider. One reason could be the present market development of computer systems applied in business. The big number of the Romanian market players determines a big number of computerized products, with a multitude of various properties. Our proposal tries to optimize and facilitate this decisional process within an e-shop where are sold IT packets applied in business, building an online decisional assistant, a special component conceived to facilitate the decision making needed for the selection of the pertinent IT package that fits the requirements of one certain business, described by the decider. The user interacts with the system as an online buyer that visit an e-shop where are sold IT package applied in economy.database, knowledge-base, decision tree, DSS, data mining, agents, reasoning, collaborative
- âŠ