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Purpose for Open-Ended Learning Robots: A Computational Taxonomy, Definition, and Operationalisation
Overall, the approach enables OEL robots to learn in an autonomous way but also to focus on acquiring goals and skills that meet the purposes of the designers and users.
Autonomous Open-Ended Learning of Tasks with Non-Stationary Interdependencies
Building on previous works, we tackle these crucial issues at the level of decision making (i. e., building strategies to properly select between goals), and we propose a hierarchical architecture that treating sub-tasks selection as a Markov Decision Process is able to properly learn interdependent skills on the basis of intrinsically generated motivations.
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