Jordan Thayer

Jordan Thayer

Total 9 Posts
Jordan completed his PhD in Artificial Intelligence at the University of New Hampshire in 2012. Since then, he's used AI to solve problems in many domains including security, medicine, & logistics.

Accidental AI: 5 Everyday AI Problems

Introduction People often ask questions like "What is AI?", or "Is AI worth of the hype?".Both questions are non-trivial to answer, but let's start with the first one:"What is AI?". This is a perennial favorite at academic conferences on AI for a few reasons: Every AI researcher has

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

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

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

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