2 papers
cs.LG2025
Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
Roberto Cipollone, Luca Iocchi, Matteo Leonetti
The main focus of Hierarchical Reinforcement Learning (HRL) is studying how large Markov Decision Processes (MDPs) can be more efficiently solved when addressed in a modular way, b…
cs.RO2019
Proceedings of the AI-HRI Symposium at AAAI-FSS 2019
Justin W. Hart, Nick DePalma, Richard G. Freedman +8
The past few years have seen rapid progress in the development of service robots. Universities and companies alike have launched major research efforts toward the deployment of amb…