Continual Learning for Robotics: Definition, Framework, Learning\n Strategies, Opportunities and Challenges

Continual learning (CL) is a particular machine learning paradigm where the\ndata distribution and learning objective changes through time, or where all the\ntraining data and objective criteria are never available at once. The evolution\nof the learning process is modeled by a sequence of learning experiences where\nthe goal is to be able to learn new skills all along the sequence without\nforgetting what has been previously learned. Continual learning also aims at\nthe same time at optimizing the memory, the computation power and the speed\nduring the learning process.\n An important challenge for machine learning is not necessarily finding\nsolutions that work in the real world but rather finding stable…