Reinforcement learning

Reinforcement Learning: Machine Learning Meets Control Theory

Reinforcement learning is a powerful technique at the intersection of machine learning and control theory, and it is inspired by how biological systems learn to interact with their environment. In this video, we provide a high level overview of reinforcement learning, along with leading a

From playlist Reinforcement Learning

Understanding Reinforcement Learning Environment and Rewards

In this video, we build on our basic understanding of reinforcement learning by exploring the workflow. We cover what an environment is and some of the benefits of training within a simulated environment. We cover what we ultimately want our agent to do and how crafting a reward function

From playlist Reinforcement Learning

Overcoming the Practical Challenges when using Reinforcement Learning

This video addresses a few challenges that occur when using reinforcement learning for production systems and provides some ways to mitigate them. Even if there aren’t straightforward ways to address some of the challenges that you’ll face, at the very least it’ll get you thinking about th

From playlist Reinforcement Learning

Reinforcement Learning Policies and Learning Algorithms

This video provides an introduction to the algorithms that reside within the agent. We’ll cover why we use neural networks to represent functions and why you may have to set up two neural networks in a powerful family of methods called actor-critic. Watch our full video series about Reinf

From playlist Reinforcement Learning

Reinforcement Learning

Reinforcement Learning

From playlist Machine Learning Course

Deep Reinforcement Learning: Neural Networks for Learning Control Laws

Deep learning is enabling tremendous breakthroughs in the power of reinforcement learning for control. From games, like chess and alpha Go, to robotic systems, deep neural networks are providing a powerful and flexible representation framework that fits naturally with reinforcement learni

From playlist Reinforcement Learning

What Is Reinforcement Learning?

In this video, we provide an overview of reinforcement learning from the perspective of an engineer. Reinforcement learning is type of machine learning that has the potential to solve some really hard control problems. Watch our full video series about Reinforcement Learning: https://you

From playlist ディープラーニング (Deep Learning — Japanese)

Introduction to Multi-Agent Reinforcement Learning

Learn what multi-agent reinforcement learning is and some of the challenges it faces and overcomes. You will also learn what an agent is and how multi-agent systems can be both cooperative and adversarial. Be walked through a grid world example to highlight some of the benefits of both de

From playlist Reinforcement Learning

Q Learning Intro/Table - Reinforcement Learning p.1

Welcome to a reinforcement learning tutorial. In this part, we're going to focus on Q-Learning. Q-Learning is a model-free form of machine learning, in the sense that the AI "agent" does not need to know or have a model of the environment that it will be in. The same algorithm can be used

From playlist Reinforcement Learning

Lecture 01: Introduction to Reinforcement Learning

Initial lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2020. Source files are available here: https://github.com/upb-lea/reinforcement_learning_course_materials

From playlist Reinforcement Learning Course: Lectures (Summer 2020)

Deep Reinforcement Learning for Fluid Dynamics and Control

Reinforcement learning based on deep learning is currently being used for impressive control of fluid dynamic systems. This video will describe recent advances, including for mimicking the behavior of birds and fish, for turbulence closure modeling with sub-grid-scale models, and for robo

From playlist Reinforcement Learning

Teaching Deep Reinforcement Learning with MATLAB

Watch this webinar by Professor Rifat Sipahi from Northeastern University to learn about the curriculum materials his team developed for teaching RL and DRL with MATLAB®. The RL modules let students implement various applications such as grid-world navigation, temperature control, walking

From playlist Teaching with MATLAB and Simulink

Introduction to Reinforcement Learning (Lecture 01, Part 1/2, Summer 2023)

Initial lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2023. Source files are available here: https://github.com/upb-lea/reinforcement_learning_course_materials 0:00 Welcome & course logistics 08:15 Course outline & recommended readings

From playlist Reinforcement Learning Course: Lectures (Summer 2023)

CMU Neural Nets for NLP 2017 (16): Reinforcement Learning

This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers: * What is Reinforcement Learning? * Policy Gradient and REINFORCE * Stabilizing Reinforcement Learning * Value-based Reinforcement Learning Slides: http://phontron.com/class/nn4nlp2017/assets/s

From playlist CMU Neural Nets for NLP 2017

Reinforcement Learning Series Intro - Syllabus Overview

Welcome to this series on reinforcement learning! We'll first start out by introducing the absolute basics to build a solid ground for us to run. We'll then progress onto more advanced and sophisticated topics that integrate artificial neural networks and deep learning into reinforcement

From playlist Reinforcement Learning - Developing Intelligent Agents

Reinforcement Learning Series: Overview of Methods

This video introduces the variety of methods for model-based and model-free reinforcement learning, including: dynamic programming, value and policy iteration, Q-learning, deep RL, TD-learning, SARSA, policy gradient optimization, among others. This is the overview in a series on reinfo

From playlist Reinforcement Learning

CS294-112 1/18/17

From playlist CS294-112 Deep Reinforcement Learning Sp17