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Concepts and Relations in Neurally Inspired In Situ Concept-Based Computing

Overview of attention for article published in Frontiers in Neurorobotics, May 2016
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Title
Concepts and Relations in Neurally Inspired In Situ Concept-Based Computing
Published in
Frontiers in Neurorobotics, May 2016
DOI 10.3389/fnbot.2016.00004
Pubmed ID
Authors

Frank van der Velde

Abstract

In situ concept-based computing is based on the notion that conceptual representations in the human brain are "in situ." In this way, they are grounded in perception and action. Examples are neuronal assemblies, whose connection structures develop over time and are distributed over different brain areas. In situ concepts representations cannot be copied or duplicated because that will disrupt their connection structure, and thus the meaning of these concepts. Higher-level cognitive processes, as found in language and reasoning, can be performed with in situ concepts by embedding them in specialized neurally inspired "blackboards." The interactions between the in situ concepts and the blackboards form the basis for in situ concept computing architectures. In these architectures, memory (concepts) and processing are interwoven, in contrast with the separation between memory and processing found in Von Neumann architectures. Because the further development of Von Neumann computing (more, faster, yet power limited) is questionable, in situ concept computing might be an alternative for concept-based computing. In situ concept computing will be illustrated with a recently developed BABI reasoning task. Neurorobotics can play an important role in the development of in situ concept computing because of the development of in situ concept representations derived in scenarios as needed for reasoning tasks. Neurorobotics would also benefit from power limited and in situ concept computing.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 25%
Researcher 2 25%
Other 1 13%
Student > Ph. D. Student 1 13%
Lecturer > Senior Lecturer 1 13%
Other 0 0%
Unknown 1 13%
Readers by discipline Count As %
Engineering 3 38%
Computer Science 2 25%
Psychology 2 25%
Agricultural and Biological Sciences 1 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2016.
All research outputs
#15,373,286
of 22,870,727 outputs
Outputs from Frontiers in Neurorobotics
#457
of 864 outputs
Outputs of similar age
#201,989
of 326,819 outputs
Outputs of similar age from Frontiers in Neurorobotics
#2
of 2 outputs
Altmetric has tracked 22,870,727 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 864 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,819 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.