Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...

Privacy professionals should pay closer attention to post-quantum cryptography as quantum-enabled attacks could eventually ...

New Iterative Block Particle Filter algorithm makes genomic surveillance faster, cheaper and more scalable, improving early ...

Classiq and Pontificia Universidad Católica de Chile (UC Chile) have announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis – assisted by classical ...

Sichkar V. N. "Reinforcement Learning Algorithms in Global Path Planning for Mobile Robot", 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi, ...

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

These include such learning paradigms as Q-Learning and the Deep Q-Networks setups. Reinforcement Learning paradigms essentially aim at teaching robots to undertake certain actions that will be used ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Space complexity of machine learning algorithms is the amount of memory or storage an algorithm requires for its successful execution. This becomes one of the important metrics of concern since it ...