'Reinforcement learning rl' presentation slideshows

Reinforcement Learning

Reinforcement Learning. HUT Spatial Intelligence course August/September 2004 Bram Bakker Computer Science, University of Amsterdam bram@science.uva.nl. Overview day 1 (Monday 13-16). Basic concepts Formalized model Value functions Learning value functions

1.45k views • 127 slides

Reinforcement Learning

Reinforcement Learning. HUT Spatial Intelligence course August/September 2004 Bram Bakker Computer Science, University of Amsterdam bram@science.uva.nl. Overview day 1 (Monday 13-16). Basic concepts Formalized model Value functions Learning value functions

1.3k views • 127 slides

uasvision /2013/11/11/ dehogaflier - uas -battles-feral-hogs/

1.51k views • 47 slides

INTRODUCTION TO ARTIFICIAL INTELLIGENCE

490 views • 36 slides

Reinforcement Learning (RL)

442 views • 35 slides

Reinforcement Learning (RL)

452 views • 35 slides

An Introduction to Reinforcement Learning (Part 1)

An Introduction to Reinforcement Learning (Part 1). Jeremy Wyatt Intelligent Robotics Lab School of Computer Science University of Birmingham jlw@cs.bham.ac.uk www.cs.bham.ac.uk/~jlw www.cs.bham.ac.uk/research/robotics. What is Reinforcement Learning (RL) ?. +3. +50. -1. -1. r 1.

475 views • 33 slides

No Metrics Are Perfect: Adversarial REward Learning for Visual Storytelling

No Metrics Are Perfect: Adversarial REward Learning for Visual Storytelling. Xin (Eric) Wang*, Wenhu Chen*, Yuan-Fang Wang, William Wang. Image Captioning. Caption: Two young kids with backpacks sitting on the porch. Visual Storytelling. Story:

222 views • 22 slides

A machine learning perspective on neural networks and learning tools

A machine learning perspective on neural networks and learning tools. Tom Schaul. Overview. PyBrain: training artificial neural networks for classification, (sequence) prediction and control Neural networks Modular structure Available architectures Training Supervised learning

211 views • 21 slides

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning. Shijiang Lu. What Is Reinforcement Learning. Reinforcement learning (RL) is the problem facing an agent that must learn how to interact on a trial and error basis with a dynamic environment so that to maximize a scalar reward. Agent. s. r. a.

145 views • 12 slides