Abstract The use of Cellular Automata (CA) in combination with Learning Automata (LA) has
demonstrated effectiveness in handling hard-to-be-solved problems. Due to their capacity to …

There is a great variety of unconventional computing approaches trying to compete with and
even surpass the classical computers in providing a solution to high complexity problems …

Computing demands are growing rapidly as bigdata and artificial intelligence applications
become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be …

One of the most prominent examples of a complex system in nature is the nervous system,
which exhibits oscillation phenomena across its structures, from single neurons to …

During the last decade, there is an ever-growing concern regarding the future of CMOS
technology, as well as the emerging difficulties on handling upcoming technological issues …

As conventional computing systems are striving to increase their performance in order to
compensate for the growing demand of solving difficult problems, emergent and …

Unconventional circuits with built-in memory and computing functionalities are becoming the
cornerstones of artificial intelligence (AI) at the edge. In the currently deployed systems …

There is a continuous urge for higher efficiency in conventional computing systems, driven
by an ever-growing demand for these systems' complexity to be able to match the one of …

Learning Automata (LA) in combination with Cellular Automata (CA) have been proven to be
viable candidates as a mean to deal with problems of high complexity. Their ability to learn …

Pattern recognition is a critical aspect of modern computing and artificial intelligence,
enabling robotic and computing systems to classify and categorize information based on its …