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THE VIDEO SHELF · game ai pathfinding

Infinite Mario AI - Long Level

A bot built by Robin Baumgarten plays Infinite Mario using A* path-finding, shown as a red planned path that updates as new obstacles appear. It won the Mario AI competitions and uses only on-screen information.

Why HN readers recommended it

HN points to it as a vivid demo that plain A* search can beat fancier machine-learning approaches in game AI.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Robin Baumgarten
Topic
game ai pathfinding
Format
demo
Level
general
HN recommenders in dataset
3
HN mentions in dataset
5
Recommendation years in dataset
2009–2012

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • If you are impressed with this one follow the link in the video to here: [VIDEO] For all my hours as a kid I was never this good, I never even realized I could kill the pipe fish by jumping from below.

    Radix on Hacker News · 2009-08
    In Mario AI competition might have a strong contender
  • Reminds me of the AI competition on infinite mario, recently: Here is a video of the winning bot (A* based approach), cool to watch, as they display its trajectory calculations. [VIDEO] GA is cool and everything, but I am sometimes sceptical about its merits. Yes, …

    feral on Hacker News · 2010-11
    In Using genetic algorithms to train a Mario AI
  • The original java infinite mario was used in the fascinating Mario AI competition. Details and papers here: [LINK] Video of last years winning entry at work here: [VIDEO] It's pretty interesting, a lot of people wrote/are writing high falutin' machine learning algorithms, but they are …

    JonnieCache on Hacker News · 2011-07
    In Infinite Mario in HTML5

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.