Robot Learning by Example

Robot Learning is the field utilizing Machine Learning and Deep Learning methods for training AI models to perform new physical skills on a robotic platform.

For any physically-intelligent mobile robot that operates autonomously in the real world, successful navigation is a critical capability.

*Reinforcement Learning (RL) represents a powerful framework for solving sequential decision-making problems in dynamic environments across diverse domains, such as control of robots or optimization of profit.

*Imagine teaching a robot to cook, drive a car, or even manage a stock portfolio.

*Deep Reinforcement Learning is a branch of machine learning, gaining rapid traction recently as an efficient approach to skills acquisition by machines, across diverse fields of applications.

*MujoCo is a physics simulator for robotics research developed by Google DeepMind and written in C++ with a Python API.

*An overview of the most prominent imitation learning methods with tests on a grid environment* *Reinforcement learning is one branch of machine learning concerned with learning by guidance of scalar signals (rewards); in contrast to supervised learning,…

Recently, (yet) another new neural network structure was proposed.

As a student or knowledge worker, time management is essential for achieving success.

*After spending some years studying and using deep learning, I always suffered from the difficulty of debugging errors, or setting hyperparameters.