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Artificial Development by Reinforcement Learning Can Benefit From Multiple Motivations
Günther Palm1, Friedhelm Schwenker1
1Institute of Neural Information Processing, Ulm University, Ulm, Germany.
Frontiers in Robotics and AI
|January 27, 2021
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.
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