AIMC Topic: Learning

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Abstract concept learning in a simple neural network inspired by the insect brain.

PLoS computational biology
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly h...

Annual Research Review: Developmental computational psychiatry.

Journal of child psychology and psychiatry, and allied disciplines
Most psychiatric disorders emerge during childhood and adolescence. This is also a period that coincides with the brain undergoing substantial growth and reorganisation. However, it remains unclear how a heightened vulnerability to psychiatric disord...

Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations.

Cognitive science
Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural networks have r...

Microanalysis of video from a robotic surgical procedure: implications for observational learning in the robotic environment.

Journal of robotic surgery
Without haptic feedback, robotic surgeons rely on visual processing to interpret the operative field. To provide guidance for teaching in this environment, we analyzed intracorporeal actions and behaviors of a robotic surgeon. Six hours of video were...

A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User.

Sensors (Basel, Switzerland)
Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learnin...

Building a knowledge base: Predicting self-derivation through integration in 6- to 10-year-olds.

Journal of experimental child psychology
Self-derivation of new factual knowledge through integration of separate episodes of learning is one means by which children build knowledge. Content generated in this manner becomes incorporated into the knowledge base and is retained over time; suc...

Priors in Animal and Artificial Intelligence: Where Does Learning Begin?

Trends in cognitive sciences
A major goal for the next generation of artificial intelligence (AI) is to build machines that are able to reason and cope with novel tasks, environments, and situations in a manner that approaches the abilities of animals. Evidence from precocial sp...

Fuzzy c-means-based architecture reduction of a probabilistic neural network.

Neural networks : the official journal of the International Neural Network Society
The efficiency of the probabilistic neural network (PNN) is very sensitive to the cardinality of a considered input data set. It results from the design of the network's pattern layer. In this layer, the neurons perform an activation on all input rec...

Machine learning in neurology: what neurologists can learn from machines and vice versa.

Journal of neurology
Artificial intelligence is increasingly becoming a part of everyday life. This raises the question whether clinical neurology can benefit from these novel methods to increase diagnostic accuracy. Several recent studies have used machine learning clas...

An End-to-End System for Automatic Urinary Particle Recognition with Convolutional Neural Network.

Journal of medical systems
The urine sediment analysis of particles in microscopic images can assist physicians in evaluating patients with renal and urinary tract diseases. Manual urine sediment examination is labor-intensive, subjective and time-consuming, and the traditiona...