**Optimal and Learning Control for Autonomous Robots**

by Jonas Buchli, et al.

**Publisher**: arXiv.org 2017**Number of pages**: 101

**Description**:

The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.

Download or read it online for free here:

**Download link**

(1.2MB, PDF)

## Similar books

**The Elements of Statistical Learning: Data Mining, Inference, and Prediction**

by

**T. Hastie, R. Tibshirani, J. Friedman**-

**Springer**

This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.

(

**37022**views)

**Reinforcement Learning**

by

**C. Weber, M. Elshaw, N. M. Mayer**-

**InTech**

This book describes and extends the scope of reinforcement learning. It also shows that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional controllers.

(

**19002**views)

**A Survey of Statistical Network Models**

by

**A. Goldenberg, A.X. Zheng, S.E. Fienberg, E.M. Airoldi**-

**arXiv**

We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.

(

**6061**views)

**Machine Learning**

by

**Abdelhamid Mellouk, Abdennacer Chebira**-

**InTech**

Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, and more.

(

**14037**views)