C951 Introduction to Artificial Intelligence

Both of these tasks ended up being largely an exercise in using buzz words for the paper. It's frustrating because it can easily be turned into something more to include machine learning which is required for capstone. I attempted to do that with Task 1 but it was taking too long to put a proper dataset and base case together. I'll have to attempt it again after graduation.

TASK 1: Start with the chapter in Ucertify called Focus: Chatbots between chapters 11 and 12. Find the exercises and hit the submit button to see examples on how to answer various parts of the rubric. For relevant data, I used O*NET which is what WGU uses for our career assessments. The Bureau of Labor Statistics can help find computer careers if you're not finding 5 distinct ones ... If you follow the rubric, this is a really primitive version of the assessments we get in the career center. My best advice is to play with different chat options. Decide your criteria that can be assessed with questions and answers, then build your conversation paths from there.

TASK 2: Start with the chapter in Ucertify called Focus: Robotics and Feature Engineering between chapters 25 and 26. Again, find the exercises and hit the submit button to see examples on how to answer various parts of the rubric. I started by building the environment to get used to the interface and object manipulation. The first thing I did was create an enclosed space to prevent Rob from falling off the testing area. Then I built a few obstacles and ran the simulation to see what Rob can do and how to improve it. I stuck with adding proximity sensors which involved copying the nose sensor and modifying the sensor name and attributes to suit my needs. Then I modified the main rob script (you'll see the nose sensor stuff in there and should be able to trace the code and use it to add the logic needed to make other sensors work). I ended up with three proximity/collision avoidance sensors that allowed rob to make right and left turns (the default only turns left). I also tweaked the speed and other attributes to force it to cover wider areas instead of getting caught in circular paths or not being able to back out of certain corners. This ended up more interesting than task 1 and I plan to make it more interesting in the future before showcasing it on GitHub.