AI Articles

We’re curious people by nature. And we love to teach others what we’ve learned. So explore our blog to gain fresh insights from our expertise in areas ranging from culture to AI.

SEP Wins TechPoint’s 2024 Innovation Service Partner of the Year Mira Award

SEP Recognized as Indiana’s Top Innovation Service Partner, Winning TechPoint’s Prestigious Mira Award Westfield, Indiana - SEP has been named the Innovation Service Partner of the Year by TechPoint at the 25th annual Mira Awards. The Mira Awards, Indiana’s largest…
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Planning for Randomizers

Introduction I’m a big fan of videogames. I like small, well defined boxes where I can get better at some task. I like measuring myself against my peers. As such, it’s probably no great surprise that I like speedrunning and randomizers. For the unititiated, speedrunning is trying to beat some game as quickly as possible. […]
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Distributing Depth First Search to the Masses

Last Time Last time we talked about techniques for exchanging processor (and developer) time for reduced will clock time in heuristic search.  In other words, we talked about how to use multiple cores on a single machine to solve a problem faster.  That worked pretty well, but we noticed that it couldn’t scale beyond the […]
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Parallel Problem Solving

Last Time Previously, we looked at a technique for reducing the memory footprint of a heuristic search. We talked about why it was important to reduce the memory consumed by a search.  Even if we move heaven and earth to reduce memory consumption, heuristic search is still prohibitively expensive in terms of time. Learning Goals This […]
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Trying Deltas For A Change

Last Time Last time we took a look at how improved bounds computation and child ordering can improve the performance of heuristic search algorithms.  In particular, we saw how those techniques improved the performance of depth first search (or depth first branch & bound if you prefer) when applied to the TSP.  Even though we […]
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The Importance of Consuming Search Results, Pancakes

Last Time Last time we looked at depth first search and how it could be applied to a simple optimization problem, the pancake problem.  We decomposed the pancake stacking problem into some components are very important if you want to apply heuristic search: A goal test States Actions to move between states We then looked […]
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Flipping Flapjacks, Pruning Pancakes, and Depth First Steps

In the previous post in this series I spent some time trying to convince you that toy problems are worthy of your attention. In particular, I tried to sell you on the notion that the pancake problem was worthy of your attention.  It isn’t necessarily because flipping flapjacks is in of itself fascinating.  It’s because […]
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Ridiculous Problems, Real Applications

Life is filled with compromises. Generally, we just don’t have the resources, be they time, money or and so on, to do the things we want to do as well as we’d like.  While I can’t solve that problem entirely or generally, I can help you intelligently trade time for improved solutions to problems that […]
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Machine Learning for Classifying Turbine Engine Performance

Introduction Machine learning is at least as old as Arthur Samuel’s attempts to improve his checkers playing programs back in the 1950s (Some Studies in Machine Learning Using the Game of Checkers), if not older still.  Despite being around for decades, machine learning has received intense interest recently from the public, the scientific community, and […]
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