Networked computing systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these en...
Abstract. When a robot learns to solve a goal-directed navigation task with reinforcement learning, the acquired strategy can usually exclusively be applied to the task that has be...
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
In this paper, we introduce new algorithms for selecting taxon samples from large evolutionary trees, maintaining uniformity and randomness, under certain new constraints on the t...
Anupam Bhattacharjee, Zalia Shams, Kazi Zakia Sult...
This work is dedicated to position control of redundant robots, realized with the help of the sensibility theory. The control method allows controlling the robot position followin...
G. Boiadjiev, D. Vassileva, Haruhisa Kawasaki, Tet...