Artificial Intelligence to predict possible life forms on other planets

Developments in artificial intelligence might facilitate us to predict the likelihood of life on different planets, according to research team from Plymouth University’s Centre for Robotics and Neural Systems used artificial neural networks (ANNs) that use similar learning techniques to the human brain, so as to estimate the likelihood of extra-terrestrial life on other worlds. It estimates the probability of life in each case, with the apparent potential to play a key role in future heavenly body exploration missions. ANNs are systems that attempt to replicate the way the human brain learns. They are particularly good at identifying patterns that are too complex for a biological brain to process and one of the main tools used in machine learning.

As per the AI system the planets are first classified into 5 different types, determined by whether they are most similar to present-day Earth, Venus, Mars or Saturn’s moon Titan. All 5 of these objects are among the most potentially habitable objects in our Solar System and are rocky bodies known to have atmospheres. The neural network uses a “probability of life” metric supported on the profile of the five target types, once a planet has been classified.

Atmospherically observed, these 5 rocky bodies of the Solar System called spectra are conferred as inputs to the network that is then asked to classify them in terms of the planetary sort. The Artificial Intelligence research team from the university trained the network with over wholly totally different spectral profiles; each with many hundred parameters that contribute to habitability, thus far the network performs well once presented with a test spectral profile that it hasn’t seen before. The technique may additionally be ideally suited to choosing targets for future observations.

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