Humans and animals can learn new skills after practicing for a few hours, while current reinforcement learning algorithms require a large amount of data to achieve good performances. Recent model-based approaches show promising results by reducing th...
This study aims to enhance the post-training evaluation of the annual performance agreement (APA) training organized by the Bangladesh Public Administration Training Centre (BPATC), the apex training institute for civil servants. Utilizing fuzzy-set ...
There is no doubt that navigating academia is a formidable challenge, particularly for those from underrepresented backgrounds who face additional barriers at every turn. In such an environment, efforts to create learning and training environments th...
Neural networks : the official journal of the International Neural Network Society
Jun 22, 2024
The brain is targeted for processing temporal sequence information. It remains largely unclear how the brain learns to store and retrieve sequence memories. Here, we study how recurrent networks of binary neurons learn sequence attractors to store pr...
Neural networks : the official journal of the International Neural Network Society
Jun 20, 2024
The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating s...
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation pro...
Neural networks : the official journal of the International Neural Network Society
Jun 18, 2024
Reinforcement learning aided by the skill conception exhibits potent capabilities in guiding autonomous agents toward acquiring meaningful behaviors. However, in the current landscape of reinforcement learning, a skill is often merely a rudimentary a...
Artificial intelligence (AI) holds immense promise for K-12 education, yet understanding the factors influencing students' engagement with AI courses remains a challenge. This study addresses this gap by extending the technology acceptance model (TAM...
Organic neuromorphic platforms have recently received growing interest for the implementation and integration of artificial and hybrid neuronal networks. Here, achieving closed-loop and learning/training processes as in the human brain is still a maj...
Exoskeletons have enormous potential to improve human locomotive performance. However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws. Here we show an experiment-free meth...