99 research outputs found
Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives
Collectiveness is an important property of many systems--both natural and
artificial. By exploiting a large number of individuals, it is often possible
to produce effects that go far beyond the capabilities of the smartest
individuals, or even to produce intelligent collective behaviour out of
not-so-intelligent individuals. Indeed, collective intelligence, namely the
capability of a group to act collectively in a seemingly intelligent way, is
increasingly often a design goal of engineered computational systems--motivated
by recent techno-scientific trends like the Internet of Things, swarm robotics,
and crowd computing, just to name a few. For several years, the collective
intelligence observed in natural and artificial systems has served as a source
of inspiration for engineering ideas, models, and mechanisms. Today, artificial
and computational collective intelligence are recognised research topics,
spanning various techniques, kinds of target systems, and application domains.
However, there is still a lot of fragmentation in the research panorama of the
topic within computer science, and the verticality of most communities and
contributions makes it difficult to extract the core underlying ideas and
frames of reference. The challenge is to identify, place in a common structure,
and ultimately connect the different areas and methods addressing intelligent
collectives. To address this gap, this paper considers a set of broad scoping
questions providing a map of collective intelligence research, mostly by the
point of view of computer scientists and engineers. Accordingly, it covers
preliminary notions, fundamental concepts, and the main research perspectives,
identifying opportunities and challenges for researchers on artificial and
computational collective intelligence engineering.Comment: This is the author's final version of the article, accepted for
publication in the Artificial Life journal. Data: 34 pages, 2 figure
A Reduced Index Mode-Independent Structure Model Transformation for Multimode Modelica Models
International audienceSince its 3.3 release, Modelica offers the possibility to specify models of dynamical systems with multiple modes having different DAE-based dynamics. However, the handling of such models by the current Modelica tools is not satisfactory, with mathematically sound models yielding exceptions at runtime. In this article, we propose a systematic way of rewriting a multimode Modelica model, based on the results of an already implemented multimode structural analysis. The rewritten Modelica model is guaranteed to be correctly compiled by state-of-the-art Modelica tools. Simulation results are presented on a simple, yet meaningful, physical system whose original Modelica model is not correctly handled by state-of-the-art Modelica tools
Digital Music Notation Data Model and Prototype Delivery System
The U.Va. Library requests $44,164 in outright funds from NEH to collaborate with the University of Paderborn in Detmold, Germany, in conducting two workshops, one to be held in summer 2009 and one in spring 2010, which will promote an international collaboration to create a music notation data model and prototype delivery system. We intend to engage a select group of international scholars and technologists with a broad range of expertise in discussing the features and functions required in a scholarly XML music notation model, critically evaluate the existing data models, discuss optimum solutions for achieving the desired features, and plan for future implementation of the solutions. Our long-term plans include applying for further grant funding to continue to develop this project after this basic collaboration is complete
Digital 3D Technologies for Humanities Research and Education: An Overview
Digital 3D modelling and visualization technologies have been widely applied to support research in the humanities since the 1980s. Since technological backgrounds, project opportunities, and methodological considerations for application are widely discussed in the literature, one of the next tasks is to validate these techniques within a wider scientific community and establish them in the culture of academic disciplines. This article resulted from a postdoctoral thesis and is intended to provide a comprehensive overview on the use of digital 3D technologies in the humanities with regards to (1) scenarios, user communities, and epistemic challenges; (2) technologies, UX design, and workflows; and (3) framework conditions as legislation, infrastructures, and teaching programs. Although the results are of relevance for 3D modelling in all humanities disciplines, the focus of our studies is on modelling of past architectural and cultural landscape objects via interpretative 3D reconstruction methods
(Leftmost-Outermost) Beta Reduction is Invariant, Indeed
Slot and van Emde Boas' weak invariance thesis states that reasonable
machines can simulate each other within a polynomially overhead in time. Is
lambda-calculus a reasonable machine? Is there a way to measure the
computational complexity of a lambda-term? This paper presents the first
complete positive answer to this long-standing problem. Moreover, our answer is
completely machine-independent and based over a standard notion in the theory
of lambda-calculus: the length of a leftmost-outermost derivation to normal
form is an invariant cost model. Such a theorem cannot be proved by directly
relating lambda-calculus with Turing machines or random access machines,
because of the size explosion problem: there are terms that in a linear number
of steps produce an exponentially long output. The first step towards the
solution is to shift to a notion of evaluation for which the length and the
size of the output are linearly related. This is done by adopting the linear
substitution calculus (LSC), a calculus of explicit substitutions modeled after
linear logic proof nets and admitting a decomposition of leftmost-outermost
derivations with the desired property. Thus, the LSC is invariant with respect
to, say, random access machines. The second step is to show that LSC is
invariant with respect to the lambda-calculus. The size explosion problem seems
to imply that this is not possible: having the same notions of normal form,
evaluation in the LSC is exponentially longer than in the lambda-calculus. We
solve such an impasse by introducing a new form of shared normal form and
shared reduction, deemed useful. Useful evaluation avoids those steps that only
unshare the output without contributing to beta-redexes, i.e. the steps that
cause the blow-up in size. The main technical contribution of the paper is
indeed the definition of useful reductions and the thorough analysis of their
properties.Comment: arXiv admin note: substantial text overlap with arXiv:1405.331
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