Developments in artificial intelligence (AI) may help us to predict the probability of life on other planets, according to a study.
Researchers at Plymouth University in the UK used artificial neural networks (ANNs) to classify planets into five types, estimating a probability of life in each case, which could be used in future interstellar exploration missions.
ANNs are systems that attempt to replicate the way the human brain learns.
They are one of the main tools used in machine learning, and are particularly good at identifying patterns that are too complex for a biological brain to process.
The team has trained the network to classify planets into five different types, based on whether they are most like the present-day Earth, the early Earth, Mars, Venus or Saturn's moon Titan.
All five of these objects are rocky bodies known to have atmospheres, and are among the most potentially habitable objects in our Solar System.
"We are currently interested in these ANNs for prioritising exploration for a hypothetical, intelligent, interstellar spacecraft scanning an exoplanet system at range," said Christopher Bishop, who presented the work at the European Week of Astronomy and Space Science (EWASS) in the UK.To read more, click here.