Juan Carlos Vargas

Sebastian Fajardo, Sina Mohammadi, Jonas Gregorio de Souza et al.

Ancient populations markedly transformed Neotropical forests, yet the spatial extent of their ecological influence remains underexplored at high resolution. Here we present a deep learning and remote sensing based approach to estimate areas of pre-Columbian forest modification based on modern vegetation. We apply this method to high-resolution satellite imagery from the Sierra Nevada de Santa Marta, Colombia, as a demonstration of a scalable approach, to evaluate palm tree distributions in relation to archaeological infrastructure. Palms were significantly more abundant near archaeological sites with large infrastructure investment. The extent of the largest palm cluster indicates that ancient human-managed areas linked to major infrastructure sites may be up to two orders of magnitude bigger than indicated by current archaeological evidence alone. Our findings suggest that pre-Columbian populations influenced vegetation, fostering conditions conducive to palm proliferation, leaving a lasting ecological footprint. This may have lowered the logistical costs of establishing infrastructure-heavy settlements in less accessible locations.

Juan Carlos Vargas, Malhar Bhoite, Amir Barati Farimani

Deep Reinforcement Learning (DRL) has emerged as a powerful control technique in robotic science. In contrast to control theory, DRL is more robust in the thorough exploration of the environment. This capability of DRL generates more human-like behaviour and intelligence when applied to the robots. To explore this capability, we designed challenging manipulation tasks to observe robots strategy to handle complex scenarios. We observed that robots not only perform tasks successfully, but also transpire a creative and non intuitive solution. We also observed robot's persistence in tasks that are close to success and its striking ability in discerning to continue or give up.