Notes

Minecraft Diamond Challenge Leaves AI Creators Stumped

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



12 December 2019



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



Microsoft is a Minecraft publisher, and other organizations challenged coders to develop AI agents that could find the sought-after gems.



The majority of people will be able to master it within their first session.



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



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



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



Even though there was no winner, one of the organizers stated that she was "hugely impressed" some of the participants.



Katja Hofmann, the principal researcher at Microsoft Research, stated that "the task we asked for was very challenging." "Finding a Minecraft diamond involves a number of steps, from cutting down trees to making tools to exploring caves to actually finding a diamond.



"While no agent submitted is competent to tackle the issue completely, they have made significant progress and learned how to use many of the tools needed."



Mining diamonds



Minecraft has grown in popularity since it was released in 2011.



More than 180 million copies of the game that is open-world have been sold, and the game has more than 112 million active monthly players.



Diamond is a very important resource in Minecraft. It can be used to create powerful weapons and armor.



To get the precious stone, 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 with the game.



The entry requirements were that the participants could only utilize one graphics processing unit (GPU), and that they undergo four days of instruction. AI systems typically require months or even years of gaming to master games like StarCraft II.



A small Minecraft dataset, comprising 60 million frames of recorded human player data, was made available to participants 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 a diamond."



Minecraft for artificial intelligence research



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The developers were asked to create programs that learned through example, the process called "imitation learning".



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



It contrasts with relying solely on "reinforcement learning" where an agent is effectively taught to find the best solution via a process of trial and error, without drawing on past knowledge.



AI for all



Researchers have found that using reinforcement learning by itself can sometimes deliver superior results.



DeepMind's AlphaGo Zero program, for instance, beat an earlier effort by the research center that utilized reinforcement learning and the analysis of labeled data from human behaviour to learn the boardgame Go.



This "pure" approach requires more computing power and is therefore too expensive for researchers who are not employed in large organizations or governments.



William Guss, a Carnegie Mellon University PhD student, was the main organizer of the contest. He said that the competition's purpose was to demonstrate that "throwing huge computations at problems isn’t necessarily the best method to push the boundaries of technology 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 large corporations that have vast areas of computing."



However, the outcome could reveal the advantages these entities with a good financial position have.
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