@mastersthesis {xCreus, title = {Unsupervised skill learning from pixels}, year = {2021}, abstract = {

This work focuses on the self-acquirement of the fundamental task-agnostic knowledge available within an environment. The aim is to discover and learn baseline representations and behaviours that can later be useful for solving embodied visual navigation downstream tasks. Specifically, the presented approach extends the idea of the "Explore, Discover and Learn" (EDL) paradigm to the pixel domain. This way, this work is centered in the representations and behaviours that can be learnt by an agent that only integrates an image capture sensor. Both the agents and the environment that is used in this work run over the Habitat AI simulator, which is developed by Facebook AI, and renders 3D fotorealistic views of the insides of apartments.





}, author = {Creus, Roger}, editor = {Nieto, Juan Jos{\'e} and Xavier Gir{\'o}-i-Nieto} }