Search Results for author:
Found 2 papers, 0 papers with code
Deep Reinforcement Learning for Motion Planning of Mobile Robots
This paper presents a novel motion and trajectory planning algorithm for nonholonomic mobile robots that uses recent advances in deep reinforcement learning.
Overcoming Catastrophic Forgetting via Hessian-free Curvature Estimates
Learning neural networks with gradient descent over a long sequence of tasks is problematic as their fine-tuning to new tasks overwrites the network weights that are important for previous tasks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
