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AI Games

Researchers Want To Use Mega Man 2 To Evaluate AI (venturebeat.com) 11

Games have long served as a training ground for AI algorithms, and not without good reason. From a report: Games -- particularly video games -- provide challenging environments against which to benchmark autonomous systems. In 2013, a team of researchers introduced the Arcade Learning Environment, a collection of over 55 Atari 2600 games designed to test a broad range of AI techniques. More recently, San Francisco research firm OpenAI detailed Procgen Benchmark, a set of 16 virtual worlds that measure how quickly models learn generalizable skills. The next frontier might be Mega Man, if an international team of researchers have their way. In a newly published paper [PDF] on the preprint server Arxiv.org, they propose EvoMan, a game-playing competition based on the eight boss fights in Capcom's cult classic Mega Man 2. As they describe it, competitors' goal is to train an AI agent to defeat every enemy and evaluate their performances by common metrics.

Why Mega Man 2? The paper's coauthors assert that few other environments test an AI's ability to win against a single enemy, or how well an AI generalizes to win matches against waves of enemies or coevolves to create increasingly difficult enemies. To this end, in EvoMan, an AI-controlled Mega Man -- a robot equipped with a powerful arm cannon -- must beat eight so-called Robot Masters equipped with different weapons. Every time a Robot Master is defeated, the agent acquires its weapon, making it easier to defeat the bosses who remain. As proposed, EvoMan challenge entrants would train their agents on any four enemies and measure how well their learned strategy scales up to a whole set of enemies. The agents would be expected to learn how to identify and react to general patterns like avoiding being shot or shooting at the direction of the enemy, and to deplete an enemy's health from 100 energy points to 0 by the end of each match.

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Researchers Want To Use Mega Man 2 To Evaluate AI

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  • Roahm Mythril did it with just the buster and no damage

  • Where Google makes progress and flashy demos, and Facebook makes progress without flashy demos (for example, Pytorch is great), OpenAI makes a lot of demos and announcements that are flashy but without any real progress. Let's not mention what the Microsoft AI team does.
  • Isn't this the plot of "The Incredibles"?

  • Make sure to include a room with all the robot masters at once, to really confirm that the AI understands each enemy's patterns and weaknesses.

  • Gotta see if it can can make those goddamned jumps properly in an "ice" or "wind" level.

  • by gl4ss ( 559668 ) on Thursday December 26, 2019 @10:22PM (#59560672) Homepage Journal

    Mega man 2 is a memory game and simple enough level wise that they will just end up training the whole game into the patter recognition.

    but really, that's what it is, a memorization game. even for human players. well that and a little bit of button smashing and reactions, but it's mainly memorization. there's not that much patterns to be learned.

    an extreme example of a really dumb game to use for AI competition would be og Rick Dangerous 1. why? it's a platformer sure, but it's 100% memorization. there's no clues for the traps. it's just a memorization game cleverly hid behind puzzle platforming facade(no, really, one of the things if you're not familiar with rick dangerous is that it's got hundreds of traps for which there is no clue, no pattern, not a single pixel of a hint that it's there - you just have to know. it becomes kinda funny even due to that).

    they should first make a mega man level and boss generator really. also I don't recall any of the bosses shooting anything that would be beneficial to catch either so that parts a bit simplistic as well.

  • by WolfgangVL ( 3494585 ) on Thursday December 26, 2019 @11:50PM (#59560812)

    It seems we're training our baby AI systems on extreme violence.

    Children only know what you teach them. Just saying....

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