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Artificial Intelligence for Robotics - Second Edition

You're reading from  Artificial Intelligence for Robotics - Second Edition

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129592
Pages 344 pages
Edition 2nd Edition
Languages
Concepts
Author (1):
Francis X. Govers III Francis X. Govers III
Profile icon Francis X. Govers III

Table of Contents (18) Chapters

Preface 1. Part 1: Building Blocks for Robotics and Artificial Intelligence
2. Chapter 1: The Foundation of Robotics and Artificial Intelligence 3. Chapter 2: Setting Up Your Robot 4. Chapter 3: Conceptualizing the Practical Robot Design Process 5. Part 2: Adding Perception, Learning, and Interaction to Robotics
6. Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning 7. Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms 8. Chapter 6: Teaching a Robot to Listen 9. Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More
10. Chapter 7: Teaching the Robot to Navigate and Avoid Stairs 11. Chapter 8: Putting Things Away 12. Chapter 9: Giving the Robot an Artificial Personality 13. Chapter 10: Conclusions and Reflections 14. Answers 15. Index 16. Other Books You May Enjoy Appendix

Introducing decision trees

The concept of a decision tree is fairly simple. You are walking down the sidewalk and come to a corner. Here, you can go right, turn left, or go straight ahead. That is your decision. After making the decision – to turn left – you now have different decisions ahead of you than if you turned right. Each decision creates paths that lead to other decisions.

As we are walking down the sidewalk, we have a goal in mind. We are not just wandering around aimlessly; we are trying to get to some goal. One or more combinations of decisions will get us to the goal. Let’s say the goal is to get to the grocery store to buy bread. There may be four or five paths down sidewalks that will get you to the store, but each path may be different in length or may have different paths. If one path goes up a hill, that may be harder than taking the level path. Another path may have you wait at a traffic light, which costs time. We assign a value to each of...

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