AUTHOR=Palm Günther , Schwenker Friedhelm TITLE=Artificial Development by Reinforcement Learning Can Benefit From Multiple Motivations JOURNAL=Frontiers in Robotics and AI VOLUME=6 YEAR=2019 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2019.00006 DOI=10.3389/frobt.2019.00006 ISSN=2296-9144 ABSTRACT=

Research on artificial development, reinforcement learning, and intrinsic motivations like curiosity could profit from the recently developed framework of multi-objective reinforcement learning. The combination of these ideas may lead to more realistic artificial models for life-long learning and goal directed behavior in animals and humans.