Minecraft Diamond Challenge Leaves AI Creators Stuck
Minecraft diamond challenge leaves AI creators stumped By Sam Shead Technology reporter
12 December 2019
It takes a few minutes for new Minecraft players to figure out how to find the diamonds that are crucial to the game, but training artificial intelligence to do this has been more difficult than anticipated.
In the summer, Minecraft publisher Microsoft and other organisations challenged coders to design AI agents that could identify the coveted gems.
Most people can master it in their first session.
However, none of the more than 660 entries submitted was up to the task.
The official announcement of the results of the MineRL competition which is the word that means "mineral" will be announced at the NeurIPSAI conference in Vancouver, Canada on Saturday.
The goal was to determine if the problem could be solved using minimal computing power.
Despite the lack of a winner however, one of the organizers said that she was "hugely amazed" by some of the participants.
"The task we set out to solve is extremely difficult," said Katja Hofmann who is a principal researcher with Microsoft Research. "Finding a Minecraft diamond is a process that involves many steps, from cutting trees to making tools , to searching caves to finally finding a gem.
"While no submitted agent has yet solved the problem completely however, they have made lot of progress and learned to make some of the tools required along the way."
Mining diamonds
Since its release in 2011, Minecraft has been wildly popular.
More than 180 million copies of the open-world game have been sold, and the title has more than 112 million active monthly players.
Diamond is one of the most important resources in Minecraft because it can be used to make powerful armour and powerful weapons.
To acquire the precious gem, however, a player must complete several other steps.
"If you're already familiar with the game it shouldn't take more than 20 minutes to get your first diamonds," Minecraft player Jules Portelly told the BBC.
The entry requirements were that the applicants could only make use of one graphics processing unit (GPU) and four days of training. AI systems usually require months or even years of gaming time to master games like StarCraft II.
A small Minecraft dataset, which contains 60 million frames of recorded human player data, was made available to entrants to help them train their systems.
"At the start of every episode they spawned in a procedurally-generated Minecraft world," explained Dr Hofmann.
"So they had to master the idea of finding resources, creating tools and then finding a gem."
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The organizers wanted the programmers to create programs that learned through example, an approach known as "imitation learning".
This is about trying to get AI agents to adopt the most effective approach by getting them to mimic what humans or other programs do to solve a task.
This is in contrast to "reinforcement learning" where an agent is trained to find the best solution by trial and trial and.
AI for all
Researchers have discovered that using reinforcement learning by itself can lead to better results.
DeepMind's AlphaGo Zero program, for instance beat an earlier attempt by the research center that utilized reinforcement learning and the analysis of labelled data from human behaviour to learn the boardgame Go.
This "pure" approach requires more computing power and is therefore too costly for researchers not working in large companies or in government.
William Guss, a Carnegie Mellon University PhD student, was the primary organizer of the contest. He explained that the purpose of the contest was to prove that "throwing huge computations at problems isn't necessarily the right way to push the boundaries of technology as a field."
He said, "It works against democratising access these reinforcement learning system and leaves the capability for agents to learn in complex environments to companies that have swathes to compute."
However, the outcome may help to highlight the advantages these well-funded entities have.
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