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ReaCog, a Minimal Cognitive Controller Based on Recruitment of Reactive Systems

Overview of attention for article published in Frontiers in Neurorobotics, January 2017
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3 X users
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1 Facebook page

Citations

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14 Dimensions

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17 Mendeley
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Title
ReaCog, a Minimal Cognitive Controller Based on Recruitment of Reactive Systems
Published in
Frontiers in Neurorobotics, January 2017
DOI 10.3389/fnbot.2017.00003
Pubmed ID
Authors

Malte Schilling, Holk Cruse

Abstract

It has often been stated that for a neuronal system to become a cognitive one, it has to be large enough. In contrast, we argue that a basic property of a cognitive system, namely the ability to plan ahead, can already be fulfilled by small neuronal systems. As a proof of concept, we propose an artificial neural network, termed reaCog, that, first, is able to deal with a specific domain of behavior (six-legged-walking). Second, we show how a minor expansion of this system enables the system to plan ahead and deploy existing behavioral elements in novel contexts in order to solve current problems. To this end, the system invents new solutions that are not possible for the reactive network. Rather these solutions result from new combinations of given memory elements. This faculty does not rely on a dedicated system being more or less independent of the reactive basis, but results from exploitation of the reactive basis by recruiting the lower-level control structures in a way that motor planning becomes possible as an internal simulation relying on internal representation being grounded in embodied experiences.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 24%
Researcher 4 24%
Other 2 12%
Student > Ph. D. Student 2 12%
Student > Bachelor 1 6%
Other 2 12%
Unknown 2 12%
Readers by discipline Count As %
Engineering 7 41%
Computer Science 2 12%
Physics and Astronomy 2 12%
Neuroscience 2 12%
Nursing and Health Professions 1 6%
Other 1 6%
Unknown 2 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 April 2017.
All research outputs
#13,531,477
of 22,947,506 outputs
Outputs from Frontiers in Neurorobotics
#269
of 871 outputs
Outputs of similar age
#211,629
of 420,054 outputs
Outputs of similar age from Frontiers in Neurorobotics
#8
of 14 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 871 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 66% of its peers.
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 420,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.