53,751 research outputs found
Organization of Multi-Agent Systems: An Overview
In complex, open, and heterogeneous environments, agents must be able to
reorganize towards the most appropriate organizations to adapt unpredictable
environment changes within Multi-Agent Systems (MAS). Types of reorganization
can be seen from two different levels. The individual agents level
(micro-level) in which an agent changes its behaviors and interactions with
other agents to adapt its local environment. And the organizational level
(macro-level) in which the whole system changes it structure by adding or
removing agents. This chapter is dedicated to overview different aspects of
what is called MAS Organization including its motivations, paradigms, models,
and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page
Twelve Theses on Reactive Rules for the Web
Reactivity, the ability to detect and react to events, is an
essential functionality in many information systems. In particular, Web
systems such as online marketplaces, adaptive (e.g., recommender) systems,
and Web services, react to events such as Web page updates or
data posted to a server.
This article investigates issues of relevance in designing high-level programming
languages dedicated to reactivity on the Web. It presents
twelve theses on features desirable for a language of reactive rules tuned
to programming Web and Semantic Web applications
Flexible programmable networking: A reflective, component-based approach
The need for programmability and adaptability in networking systems is becoming increasingly important. More specifically, the challenge is in the ability to add services rapidly, and be able to deploy, configure and reconfigure them as easily as possible. Such demand is creating a considerable shift in the way networks are expected to operate in the future. This is the main aim of programmable networking research community, and in our project we are investigating a component-based approach to the structuring of programmable networking software. Our intention is to apply the notion of components, component frameworks and reflection ubiquitously, thus accommodating all the different elements that comprise a programmable networking system
Designing as Construction of Representations: A Dynamic Viewpoint in Cognitive Design Research
This article presents a cognitively oriented viewpoint on design. It focuses
on cognitive, dynamic aspects of real design, i.e., the actual cognitive
activity implemented by designers during their work on professional design
projects. Rather than conceiving de-signing as problem solving - Simon's
symbolic information processing (SIP) approach - or as a reflective practice or
some other form of situated activity - the situativity (SIT) approach - we
consider that, from a cognitive viewpoint, designing is most appropriately
characterised as a construction of representations. After a critical discussion
of the SIP and SIT approaches to design, we present our view-point. This
presentation concerns the evolving nature of representations regarding levels
of abstraction and degrees of precision, the function of external
representations, and specific qualities of representation in collective design.
Designing is described at three levels: the organisation of the activity, its
strategies, and its design-representation construction activities (different
ways to generate, trans-form, and evaluate representations). Even if we adopt a
"generic design" stance, we claim that design can take different forms
depending on the nature of the artefact, and we propose some candidates for
dimensions that allow a distinction to be made between these forms of design.
We discuss the potential specificity of HCI design, and the lack of cognitive
design research occupied with the quality of design. We close our discussion of
representational structures and activities by an outline of some directions
regarding their functional linkages
Knowledge formalization in experience feedback processes : an ontology-based approach
Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable
"Going back to our roots": second generation biocomputing
Researchers in the field of biocomputing have, for many years, successfully
"harvested and exploited" the natural world for inspiration in developing
systems that are robust, adaptable and capable of generating novel and even
"creative" solutions to human-defined problems. However, in this position paper
we argue that the time has now come for a reassessment of how we exploit
biology to generate new computational systems. Previous solutions (the "first
generation" of biocomputing techniques), whilst reasonably effective, are crude
analogues of actual biological systems. We believe that a new, inherently
inter-disciplinary approach is needed for the development of the emerging
"second generation" of bio-inspired methods. This new modus operandi will
require much closer interaction between the engineering and life sciences
communities, as well as a bidirectional flow of concepts, applications and
expertise. We support our argument by examining, in this new light, three
existing areas of biocomputing (genetic programming, artificial immune systems
and evolvable hardware), as well as an emerging area (natural genetic
engineering) which may provide useful pointers as to the way forward.Comment: Submitted to the International Journal of Unconventional Computin
Curriculum Guidelines for Undergraduate Programs in Data Science
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
- âŠ