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Selection: with tag artificial-intelligence [15 articles] 


What can machine learning do? Workforce implications

Science, Vol. 358, No. 6370. (22 December 2017), pp. 1530-1534,


Digital computers have transformed work in almost every sector of the economy over the past several decades (1). We are now at the beginning of an even larger and more rapid transformation due to recent advances in machine learning (ML), which is capable of accelerating the pace of automation itself. However, although it is clear that ML is a “general purpose technology,” like the steam engine and electricity, which spawns a plethora of additional innovations and capabilities (2), there is no ...


Reboot for the AI revolution

Nature, Vol. 550, No. 7676. (17 October 2017), pp. 324-327,


As artificial intelligence puts many out of work, we must forge new economic, social and educational systems, argues Yuval Noah Harari. [Excerpt] The ongoing artificial-intelligence revolution will change almost every line of work, creating enormous social and economic opportunities — and challenges. Some believe that intelligent computers will push humans out of the job market and create a new 'useless class'; others maintain that automation will generate a wide range of new human jobs and greater prosperity for all. Almost everybody agrees ...


The challenge of knowledge soup

In Research Trends in Science, Technology and Mathematics Education (May 2006), pp. 55-90


People have a natural desire to organize, classify, label, and define the things, events, and patterns of their daily lives. But their best-laid plans are overwhelmed by the inevitable change, growth, innovation, progress, evolution, diversity, and entropy. These rapid changes, which create difficulties for people, are far more disruptive for the fragile databases and knowledge bases in computer systems. The term knowledge soup better characterizes the fluid, dynamically changing nature of the information that people learn, reason about, act upon, and ...


A horizon scan of global conservation issues for 2016

Trends in Ecology & Evolution, Vol. 31, No. 1. (January 2016), pp. 44-53,


This paper presents the results of our seventh annual horizon scan, in which we aimed to identify issues that could have substantial effects on global biological diversity in the future, but are not currently widely well known or understood within the conservation community. Fifteen issues were identified by a team that included researchers, practitioners, professional horizon scanners, and journalists. The topics include use of managed bees as transporters of biological control agents, artificial superintelligence, electric pulse trawling, testosterone in the aquatic ...


Stephen Hawking: 'Transcendence looks at the implications of artificial intelligence - but are we taking AI seriously enough?'

The Independent, Vol. 2014, No. 05-01. (1 May 2014), 9313474


Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks, says a group of leading scientists. [Excerpt] Artificial-intelligence (AI) research is now progressing rapidly. Recent landmarks such as self-driving cars, a computer winning at Jeopardy! and the digital personal assistants Siri, Google Now and Cortana are merely symptoms of an IT arms race fuelled by unprecedented investments and building on an increasingly mature theoretical foundation. ...


Research priorities for robust and beneficial artificial intelligence

(January 2015)


[Executive Summary] Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to research how to maximize these benefits while avoiding potential pitfalls. This document gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial. [Research Priorities for Robust and Beneficial Artificial Intelligence: an Open Letter] Artificial intelligence (AI) research has explored a variety of problems and approaches since ...


Neural Turing machines

(10 Dec 2014)


We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples. ...

Visual summary


A Decision-Theoretic Model of Assistance

Journal of Artificial Intelligence Research, Vol. 50 (2014), pp. 71-104,


There is a growing interest in intelligent assistants for a variety of applications from sorting email to helping people with disabilities to do their daily chores. In this paper, we formulate the problem of intelligent assistance in a decision-theoretic framework, and present both theoretical and empirical results. We first introduce a class of POMDPs called hidden-goal MDPs (HGMDPs), which formalizes the problem of interactively assisting an agent whose goal is hidden and whose actions are observable. In spite of its restricted ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 3

(February 2014)
Keywords: apennines   aphid   aphis-pomi   apl   apmv-transmission   approximate-dynamic-programming   apriona-germari   aqua-modis   aquatic-invertebrate-shredders   aradus-cinnamommeus   araucaria-angustifolia   araucaria-araucana   araucaria-bidwillii   araucaria-heterophylla   araucaria-montana   araucaria-spp   arboriculture   arbutus-canariensis   arbutus-menziesii   arbutus-spp   arbutus-unedo   arctic-region   arctostaphylos-uva-ursi   ardity   argania-spinosa   argentina   argive-plain   arid-climate   arid-region   aridity   arion-lusitanicus   aristolochia-arborea   armillaria-spp   array-atomic-variables   array-of-agents   array-of-factors   array-of-sectors   array-of-users   array-programming   arsenic   arthropods   artic-region   artic-sea-ice   artificial-intelligence   artificial-neural-network   artificial-neural-networks   artocarpus-altilis   artocarpus-heterophyllus   arvicola-spp   arxiv   asia   aspidosperma-cruentum   aspidosperma-myristicifolium   asplenium-spp   assessment   associated-microorganisms   association-genetics   associations   asteraceae   asynchronous-change   atmosphere   atmospheric-circulation   atriplex-halimus   atriplex-nummularia   atta-cephalotes   auc   australia   austria   austrocedrus-chilensis   authorship   autoecology   automatic-knowledge-generation   automatic-knowledge-mapping   automation   automation-irony   autonomic-computing   autoregressive-model   avicennia-germinans   avifauna   awk   azadirachta-indica   azerbaijan   azolla-spp   bacillus-thuringiensis   back-propagation-networks   bacteria   bacterial-canker   bacterial-diseases   bacterial-wood-degradation   bactris-gasipaes   bactrocera-invadens   bactrocera-oleae   baikiaea-plurijuga   balanites-aegyptiaca   balkan-peninsula   balkan-region   balkans   bangladesh   banksia-grandis   inrmm-list-of-tags  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


Expert system & knowledge engineering in Wikipedia

In Compilation (September 2012)
edited by Mohsen Kahani


Compilation of topics published in Wikipedia on Expert System and Knowledge Engineering: Expert system; Knowledge representation and reasoning, Reasoning system; Forward chaining; Rete algorithm; Backward chaining; Backward induction; Production system; Production Rule Representation; Inference engine; Fuzzy logic; Fuzzy control system; Artificial neural network; Types of artificial neural networks; Feedforward neural network; Self-organizing map; Hybrid intelligent system; Neuro-fuzzy; Genetic fuzzy systems; Knowledge engineering; Knowledge retrieval; Knowledge acquisition; Knowledge management; Data warehouse; Extract, transform, load; Star schema; Snowflake schema; Data mining; Cross Industry Standard Process for Data Mining; Statistical classification; Cluster analysis; Association rule learning; Sequence mining; Anomaly detection. ...


Novel methods improve prediction of species' distributions from occurrence data

Ecography, Vol. 29, No. 2. (1 April 2006), pp. 129-151,


Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only ...


Connecting the dots my own way: sphex-test and flexibility in artificial cognitive agents

In Towards a Comprehensive Intelligence Test (TCIT): Reconsidering the Turing Test for the 21st Century Symposium (2010)


The purpose of this paper is to raise doubts on the standard approach in cognitive science regarding the design of artificial intelligence. An intelligence criterion, different from the Turing test, is presented and explained: the sphex-test. Following the explanation of the test, a theoretical approach of the normative constraints of experimental setups is presented and the causes of failure determined through it. It is shown that domains with which the agent can only relate in one unique way (have only one ...


AIGIS-based methodology for natural terrain landslide susceptibilitymapping in Hong Kong

Episodes, Vol. 24, No. 3. (2001), pp. 150-158


This paper presents a novel application of Artificial Intelligence (AI) and Geographic Information System (GIS) to the mapping of natural terrain landslide susceptibility in Hong Kong. The method is applied to the central part of Lantau Island as a pilot study. First, we discuss the key technical concepts of AI and GIS, the advantages of their integrated application, and the growing importance of remote sensing data. We then describe the working procedure including the construction of the GIS database, pre-treatment of ...


Automatic programming: myths and prospects

Computer, Vol. 21, No. 8. (August 1988), pp. 40-51,


The authors consider five common myths about automatic programming and expose the fallacies on which they rest. They attempt to provide an accurate picture of these systems in terms of what the user sees, how the system works, and what the system knows. They describe commercially available systems and discuss what is on the horizon.> ...


The Semantic Web: The Origins of Artificial Intelligence Redux

In Third International Workshop on the History and Philosophy of Logic, Mathematics and Computation (HPLMC-04 2005) (2005)


Introduction. The World Wide Web is considered by many to be the most significant computational phenomenon yet, although even by the standards of computer science its development has been chaotic. While the promise of artificial intelligence to give us machines capable of genuine human-level intelligence seems nearly as distant as it was during the heyday of the field, the ubiquity of the World Wide Web is unquestionable. If anything it is the Web, not artificial intelligence as traditionally conceived, that has ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database.

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Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.