AIMC Topic: Learning

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Training memristor-based multilayer neuromorphic networks with SGD, momentum and adaptive learning rates.

Neural networks : the official journal of the International Neural Network Society
Neural networks implemented with traditional hardware face inherent limitation of memory latency. Specifically, the processing units like GPUs, FPGAs, and customized ASICs, must wait for inputs to read from memory and outputs to write back. This moti...

Network Dynamics Governed by Lyapunov Functions: From Memory to Classification.

Trends in neurosciences
In 1982, John Hopfield published a neural network model for memory retrieval, a model that became a cornerstone in theoretical neuroscience. In a recent paper, Krotov and Hopfield built on these early studies and showed how a network that incorporate...

Deep Multi-Critic Network for accelerating Policy Learning in multi-agent environments.

Neural networks : the official journal of the International Neural Network Society
Humans live among other humans, not in isolation. Therefore, the ability to learn and behave in multi-agent environments is essential for any autonomous system that intends to interact with people. Due to the presence of multiple simultaneous learner...

Phase portraits as movement primitives for fast humanoid robot control.

Neural networks : the official journal of the International Neural Network Society
Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensitive to model accuracy. On the other hand, animals plan complex motor a...

Machine learning identifies the dynamics and influencing factors in an auditory category learning experiment.

Scientific reports
Human learning is one of the main topics in psychology and cognitive neuroscience. The analysis of experimental data, e.g. from category learning experiments, is a major challenge due to confounding factors related to perceptual processing, feedback ...

Artificial Intelligence and Persuasion: A Construal-Level Account.

Psychological science
Although more individuals are relying on information provided by nonhuman agents, such as artificial intelligence and robots, little research has examined how persuasion attempts made by nonhuman agents might differ from persuasion attempts made by h...

Developing an Interactive Environment Through the Teaching of Mathematics with Small Robots.

Sensors (Basel, Switzerland)
The article is the product of the study "Development of innovative resources to improve logical-mathematical skills in primary school, through educational robotics", developed during the 2019 school year in three public schools in the province of Chi...

Assessing the environmental quality of an adapted, play-based LEGO robotics program to achieve optimal outcomes for children with disabilities.

Disability and rehabilitation
PURPOSE: This study assessed the environmental quality of an adapted, play-based LEGO robotics program for children and youth with disabilities to determine the degree to which the activity setting supports the therapeutic goals of the program.

Explainable decision support through the learning and visualization of preferences from a formal ontology of antibiotic treatments.

Journal of biomedical informatics
The aim of eXplainable Artificial Intelligence (XAI) is to design intelligent systems that can explain their predictions or recommendations to humans. Such systems are particularly desirable for therapeutic decision support, because physicians need t...

Real-time sensory-motor integration of hippocampal place cell replay and prefrontal sequence learning in simulated and physical rat robots for novel path optimization.

Biological cybernetics
An open problem in the cognitive dimensions of navigation concerns how previous exploratory experience is reorganized in order to allow the creation of novel efficient navigation trajectories. This behavior is revealed in the "traveling salesrat prob...