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Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In evolutionary reinforcement learning, an intelligent agent learns optimal strategies by actively exploring different approaches and receiving rewards for successful performance. This innovative paradigm combines reinforcement learning's trial-and-error learning with evolutionary algorithms' ability to mimic natural selection, resulting in a powerful methodology for artificial intelligence developmen...

Clouds play a crucial role in regulating Earth’s climate, impacting the water cycle, atmospheric dynamics, and energy balance. Studying them, however, has been challenging due to limitations in spaceborne imaging technology. Researchers from the Technion have developed an efficient inverse rendering

A machine learning model has been proven effective as a decision-support tool for dispatchers of Emergency Medical Services (EMS), resulting in improved triage quality and ambulance utilization, according to a study done in Singapore.

Even though electron microscopy could already disclose details as small as one nanometer, existing research aims to break through barriers restricting image quality and decreasing the optical dose present in the samples.

Although electron microscopy can already reveal details as small as one nanometer, ongoing research seeks to break through barriers limiting image quality and reducing the optical dose on the samples. Aberration is a common problem in electron microscopy that can reduce the resolution and quality of the images produced.