Narrow, inextensible, and naturally flat ribbons have some special and interesting
phenomena under isometric deformations. Although a ribbon has a shape between rod and …

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse
of dimensionality, and environment non-stationarity due to the independent learning …

Performing reinforcement learning-based control of systems whose state space has many
Undesired Terminal States (UTS) experiences severe convergence problems. We define …

Multiagent systems are increasingly present in computational environments. However, the
problem of agent design or control is an open research field. Reinforcement learning …

Autonomous task learning for Linked Multicomponent Robotic Systems (L-MCRS) is an
open research issue. Pilot studies applying Reinforcement Learning (RL) on Single Robot …

Despite the long R&D history of interactive minimally-invasive surgery and therapy
simulations, the guide wire/catheter behavior modeling remains challenging in …

In this paper we address the physical realization of proof of concept experiments
demonstrating the suitability of the controllers learned by means of Reinforcement Learning …

Improvements in quality and safety standards in surgical training, reduction in training hours
and constant technological advances have challenged the traditional apprenticeship model …