Sessions

Heuristic search is a discipline under the larger umbrella in AI. Heuristic search algorithms find solutions to a variety of problems, including pathfinding, logistics, and scheduling. Most of the problems heuristic search is applied to are hard in the formal sense. This forces us to find new techniques to tackle larger problems and new domains — we can’t simply wait for improved
hardware to solve it for us. When developing new AI algorithms, understanding what has come before and why it fails to perform in a new domain is critical. In this talk, we’ll look at how algorithm visualization drove the development of state of the art AI algorithms for heuristic search.

Key takeaways from the session:

• I hope to impress people with the idea that the first step to improving anything, even the state of the art in a field, is to build an intimate understanding of that thing.
• Second, that visualizations are an important tool in building an understanding of the behavior of a thing, in this case an algorithm.
• Finally, that AI isn’t science fiction. The simplest algorithms are accessible to anyone that wants to invest time in understanding how AI interacts with the world around us.