Notes

Minecraft Diamond Challenge Leaves AI Creators Stumped

Minecraft diamond challenge leaves AI creators confused By Sam Shead Technology reporter



12 December 2019



It takes minutes for most new Minecraft players to figure out how to find the diamonds that are key to the game, but training artificial intelligence to do this has been more difficult than anticipated.



Over the summer, Minecraft publisher Microsoft and other organizations challenged developers to design AI agents that could locate the sought-after gems.



Most people can master it in their first attempt.



Of the 660 entries, only one could have performed the task.



The results of the MineRL - a well-known mineral-related - competition are scheduled to be announced formally on Saturday at the NeurIPS AI conference in Vancouver, Canada.



The aim had been to determine whether the issue could be solved without requiring massive amounts of computing power.



Despite not having a winner, one organiser said that she was still "hugely amazed by" some of the participants.



"The task we posed is very hard," said Katja Hofmann who is a principal researcher with Microsoft Research. "Finding diamonds in Minecraft requires a variety of steps ranging from cutting down trees, making tools to exploring caves and actually finding diamonds.



"While no agent has yet solved the problem completely but they have made a lot of progress and developed many of the tools needed in the process."



Mining diamonds



Since its release in 2011 Minecraft has been wildly popular.



The open-world game has been downloaded more than 180 million times, and the title is played by more than 112 million people every month.



Diamond is among the most important resources found in Minecraft because it can be used to build strong armour and powerful weapons.



To obtain the precious gemstone, however, a player must go through a few other steps.



"If you're familiar with the game, it shouldn't take more than 20 minutes to get your first diamonds," Minecraft player Jules Portelly told the BBC.



Entrants were only allowed to make use of a single graphics processing unit (GPU) and four days of training. For context, AI systems usually need months or years of game play to master games such as StarCraft II.



To train their systems, a relatively small Minecraft dataset comprising 60 million frames of player data was made available to entrants.



"At the start of every episode they spawned in a procedurally-generated Minecraft world," explained Dr Hofmann.



"So they had to learn the idea of finding resources, making tools and finding a treasure."



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The organisers wanted the coders to develop programs that learn by imitation, using the process known as "imitation learning".



This is where you try to make AI agents to take the best method of solving a problem by making them imitate humans or other software.



This contrasts with "reinforcement learning" where an agent is trained to find the most effective solution through trial and error.



All AI



Research has proven that reinforcement learning can produce superior results.



DeepMind's AlphaGo Zero program, for instance beat an earlier attempt by the research hub that used reinforcement learning and the analysis of data labelled from human behavior 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.
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William Guss, the main organizer of the competition and a PhD student at Carnegie Mellon University, told the BBC that the goal of the contest was to demonstrate that "throwing massive computing at problems isn't the best way to push the limits of the art in a field".



He said, "It works against democratising access these reinforcement learning system, and leaves the ability for agents to train in complex environments to companies that have vast areas of computing."



However, the outcome may highlight the advantages these well-funded entities have.



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