Someone has the concept of "extraterrestrial life" associated with ET or gray people from the X-Files series, someone believes in it wholeheartedly. The truth is that the regions beyond our planet are so vast and so unexplored that it is difficult to unequivocally confirm or deny the possibility of such life. What can artificial intelligence do in this direction?
Artificial intelligence could help astronomers search for extraterrestrial life, according to new research from the University of Plymouth in the UK. Scientists are currently working hard to "train" so-called artificial intelligenceseuronew networks (ANN) to predict the probability of life on other planets. They hope that this will help determine other targets for future space missions. The results of the work should be published today on European Week of Astronomy and Space Science in Liverpool.
"We are currently interested in these networks (ANNs) because of the possible hypothetical monitoring of exoplanetary systems by intelligent interplanetary devices," said Christopher Bishop, a researcher at the Center for Robotics andeuronew systems at the University of Plymouth.
ANN networks represent a computing system capable of imitating the learning processes taking place in the human brain. These networks are particularly useful when identifying complex patterns in large amounts of data, a task that can be very time consuming especially for "human" scientists. An ANN that could predict the habitability of a larger number of planets could thus save scientists time and help them focus on only the most promising targets.
A team from Plymouth University taught the appropriate neuronew network to classify planets into five different categories based on whether they are more similar to present-day Earth, early Earth, Mars, Venuor Titan – the largest moon of the planet Saturn.
The common feature of these environments is their rocky surface and atmosphere. Besides Earth, Mars and Titan represent some of the most promising targets in the search for extraterrestrial life within our solar system. According to some scientists, they may also VenuDespite the high temperature, it still offers suitable conditions for life.
The researchers fed the respective networks the results of observations from the above environments and then asked them to classify them using a "probability of life" measure. Thanks to this data, the networks can then take over data from other environments and determine the possibility of the occurrence of life in them.
"Based on the results so far, this method can be extremely useful in categorizing different types of exoplanets using results from ground-based and near-Earth observatories," said Angelo Cangelosi, project leader.
The researchers hope that their technique will prove particularly useful in upcoming space missions, such as the European Space Agency's Ariel Space Mission.
Source: Newsweek
