Notes

Minecraft Diamond Challenge Leaves AI Creators Stumped

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



12 December 2019



The majority of Minecraft players can find the key diamonds in minutes. However, it's much more difficult to create artificial intelligence that can do this task.



In the summer, Minecraft publisher Microsoft and other organisations challenged coders to create AI agents that could locate the most sought-after gems.



Most people can master it in their first session.



However there was no way to prove that any of the more than 660 entries submitted met the challenge.



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



The goal was to determine if the issue could be solved with minimal computing power.



Despite not having a winner, one organizer said that she was still "hugely impressed" some of the participants.



"The task we posed is extremely difficult," said Katja Hofmann, a principal researcher at Microsoft Research. "Finding a Minecraft diamond involves a number of steps, from cutting down trees to making tools , to exploring caves to actually finding a gem.



"While the submitted agents aren't able to solve the task completely, they have made significant progress and have learned how to utilize many of the tools needed."



Mining diamonds



Since its launch in 2011, Minecraft has become a hugely popular game.



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



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



However, to acquire the precious stone, a player must first go through a series of 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 utilize a single graphics processor unit (GPU) and four days of training. For context, AI systems usually need months or even years of gaming time to master games such as StarCraft II.



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



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



"So they really had to understand the idea of locating resources creating tools and locating diamonds."



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The developers were asked to create programs that were learned by imitation, a technique called "imitation learning".



This is where you attempt to get AI agents adopt the best method of solving a problem by allowing them to mimic humans or other software.



It is in contrast to relying entirely on "reinforcement learning" where an agent is trained to determine the most effective solution through trial and error, not using previous knowledge.



AI for all



Research has shown that reinforcement learning can lead to superior results.



For instance, DeepMind's AlphaGo Zero program trumped one of the hub's earlier initiatives, which employed reinforcement learning and the study of labelled data from human play to learn the game of Go.



However, this "pure" method usually requires much more computing power, which makes it too costly for researchers outside of large organizations or government agencies.



William Guss, a Carnegie Mellon University PhD student, was the main organizer of the competition. He stated that the competition's purpose was to show that "throwing huge computations at problems isn’t necessarily the best method to advance the state of the art as a discipline."



He said, "It works against democratising access these reinforcement learning system and leaves the capacity to train agents in complex environments to corporations that have vast areas of computing."
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However, the outcome could reveal the advantages these well-funded entities have.



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