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Minecraft Diamond Challenge Leaves AI Creators Stuck

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



12 December 2019



The majority of Minecraft players can locate the key diamonds in minutes. However, it is much more difficult to train artificial intelligence to do this job.



Microsoft is an Minecraft publisher and other companies challenged coders to develop AI agents that could identify the sought-after gems.



Most can crack it in their first session.



Of the 660 entries, only one of them was up to the task.



The official announcement of the results of the MineRL competition which is pronounced "mineral" will be made at the NeurIPSAI conference in Vancouver, Canada on Saturday.



The goal was to determine if the problem could be solved with a minimum of computing power.



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



"The task we set out to solve is very hard," 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 creating tools, from exploring caves and finally finding a diamond.
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"While no submitted agent has fully solved the task however, they have made lot of progress and made many of the tools needed along the way."



Mining diamonds



Since its debut 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 game is played by more than 112,000,000 players every month.



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



To acquire the precious gem, however, a player must follow a number of other steps.



Jules Portelly, a Minecraft player, said it shouldn't take more than 20 minutes to earn your first diamonds, if you're comfortable playing the game.



Entrants were only allowed to make use of a single graphics processing unit (GPU) and four days of training. AI systems typically require months or even years of gaming time to master games such as StarCraft II.



A comparatively small Minecraft dataset, which contains 60 million frames of human player data, was provided to players 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 really had to be able to comprehend the idea of locating resources, making tools , and finding the diamond."



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The organizers wanted the programmers to develop programs that learn through example, a technique known as "imitation learning".



This is where you try to make AI agents to adopt the most effective approach to solve a problem by getting them to imitate humans or other software.



This is in contrast to "reinforcement learning" where agents are trained to find the most effective solution through trial and error.



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Researchers have discovered that using reinforcement learning by itself can produce superior results.



For instance, DeepMind's AlphaGo Zero program trumped one of the research hub's previous initiatives, which employed reinforcement learning and the study of labelled data from human interaction to teach the board game Go.



This "pure" method requires more computing power and is therefore too costly for researchers not working in large organisations or government agencies.



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 computation at problems isn't necessarily the right way for us to push the boundaries of the art in the field".



He added, "It works against democratising access to these systems of reinforcement learning and leaves the capacity to train agents in complex environments to corporations that have swathes to compute."



However, the outcome may be a good indicator of the advantages these organizations with good funding have.



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