General in-hand object rotation with vision and touch
We introduce Rotateit, a system that enables fingertip-based object rotation along multiple
axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it …
axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it …
Cal-ql: Calibrated offline rl pre-training for efficient online fine-tuning
A compelling use case of offline reinforcement learning (RL) is to obtain a policy initialization
from existing datasets followed by fast online fine-tuning with limited interaction. However …
from existing datasets followed by fast online fine-tuning with limited interaction. However …
A survey on explainable ai for 6g o-ran: Architecture, use cases, challenges and research directions
B Brik, H Chergui, L Zanzi, F Devoti, A Ksentini… - ar** in advancing reinforcement learning applications
Reinforcement Learning (RL) seeks to develop systems capable of autonomous decision-
making by learning through interaction with their environment. Central to this process are …
making by learning through interaction with their environment. Central to this process are …