People solve many problems every day. Maybe we’re figuring out what we should wear to some party or maybe we’re coming up with the best way to drive to some place. Sometimes we’re even trying to figure out who we should marry or where we should go to college.

When a person solves a difficult problem involving many different factors, they make a tradeoff without even realizing it. If we spend too little time solving the problem, we end up with a solution that just isn’t good enough. …

I’m currently a teaching assistant for the graduate-level AI class taught by my advisor Shlomo Zilberstein at UMass Amherst. In one of the homework assignments, the students had to write some code that solves sudoku puzzles. This means I’ve been talking about how to use AI algorithms to solve sudoku way too much lately. Because it’s fresh on my mind, I figured I’d write a quick and dirty blog post that discusses how we can use a simple AI algorithm to solve sudoku puzzles and similar games.

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Photo by Marijakes on Pixabay

Before getting to sudoku, let’s go over a traditional example in AI, which is a rite of passage at this point. Suppose we have to color a map with different colors where no two neighboring regions can have the same color. Simply put, we just need to paint each region of the map a different color and none of the regions that neighbor each other can have the same color. For example, let’s say we want to color the paradigmatic example of Australia that’s used in practically every AI…

Recently, I’ve been working on my own mobile robot, Pumpkin, with a Master’s student in my research lab. Since we’re trying to replace some of the default packages that my robot uses from the library ROS, we’ve been learning about different algorithms used throughout a typical robot stack. …


Justin Svegliato

CS PhD student at UMass Amherst. Former software developer on Wall Street. I build autonomous systems that reason and learn.

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