- What are the three ways to traverse a decision tree?
- In the Fishbone diagram example, how does one go about pruning the branches of the decision tree?
- What is the role of the Gini evaluator in creating a classification?
- In the toy classifier example using Gini indexing, which attributes of the toy were not used by the decision tree? Why not?
- Which color for the toys was used as a criteria by one of the classification techniques we tried?
- Give an example of label encoding and one hot encoding for menu items at a restaurant.
- In the A* algorithm, discuss the different ways that G() and H() are computed.
- In the A* algorithm, why is H() considered a heuristic and G() is not. Also, in the D* algorithm, heuristics are not used. Why not?
- In the D* algorithm, why is there a RAISED and a LOWERED tag and not just a CHANGED flag?
Artificial Intelligence for Robotics
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Artificial Intelligence for Robotics
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Overview of this book
Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills.
As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks.
By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence.
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Current Title:
Artificial Intelligence for Robotics
Table of Contents (13 chapters)
Preface
Free Chapter
Foundation for Advanced Robotics and AI
Setting Up Your Robot
A Concept for a Practical Robot Design Process
Object Recognition Using Neural Networks and Supervised Learning
Picking up the Toys
Teaching a Robot to Listen
Avoiding the Stairs
Putting Things Away
Giving the Robot an Artificial Personality
Conclusions and Reflections
Assessments
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