Evolutionary algorithms (EAs) have long provided a flexible framework for solving challenging optimisation problems by mimicking natural evolutionary processes. When combined with multitask ...

Constantly "re-rolling the dice", combining and selecting: "Evolutionary algorithms" mimic natural evolution in silico and lead to innovative solutions for complex problems. Constantly “re-rolling the ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Does evolutionary computation ring a bell? In computer science, it’s the ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The promise of evolutionary algorithms has been around for several years, ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...

Dr. James McCaffrey of Microsoft Research explains stochastic gradient descent (SGD) neural network training, specifically implementing a bio-inspired optimization technique called differential ...

With all the excitement over neural networks and deep-learning techniques, it’s easy to imagine that the world of computer science consists of little else. Neural networks, after all, have begun to ...

Uncovering the mechanisms of learning via synaptic plasticity is a critical step towards understanding how our brains function and building truly intelligent, adaptive machines. Researchers propose a ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...