Artificial Intelligence (AI) will soon be used to search for extraterrestrial life on other planets, according to researchers from the Centre for Robotics and Neural Systems (CRNS), Plymouth University.
The research team has developed an A.I. system that is able to predict the likelihood of life on exoplanets. The intelligent tool will help researchers identify and focus on the exoplanet which is worth exploring as opposed to studying every single one discovered. The research work will be presented at the European Week of Astronomy and Space Science (EWASS) in Liverpool on Wednesday, April 4.
Scientists have made use of artificial intelligence and artificial neural networks (ANNs) to classify five planet types in terms of their life-supporting feature. Artificial neural networks are systems that replicate the way the human brain learns.
The five planet categories have been classified depending on their similarities to present-day Earth, early Earth, Mars, Venus, or Saturn’s moon Titan. All these five celestial bodies have a rocky composition and are among the most potentially habitable planets in the Solar System.
The research team used NASA’s Planetary Spectrum Generator (PSG) at the Goddard Space Flight Center to feed the ANN with atmospheric observations, also known as spectra, of the five Solar System bodies and then asked the system to classify them in terms of the planetary type.
Lead study author Mr. Christopher Bishop explained that the research team is currently interested in these ANNs for prioritizing exploration for a hypothetical, intelligent, interstellar spacecraft scanning an exoplanet system at a range.
The network has performed quite well so far when presented with a test spectral profile that it hasn’t seen before. The researchers are hopeful that the AI technique may be used with data from upcoming space missions including NASA’s James Webb Space Telescope and ESA’s Ariel Space Mission to search for extraterrestrial life in target prospective planets.