{"id":685122,"date":"2020-08-20T14:48:48","date_gmt":"2020-08-20T21:48:48","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?p=685122"},"modified":"2020-10-06T16:10:08","modified_gmt":"2020-10-06T23:10:08","slug":"minerl-sample-efficient-reinforcement-learning-challenge-back-for-a-second-year-benefits-organizers-as-well-as-larger-research-community","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/minerl-sample-efficient-reinforcement-learning-challenge-back-for-a-second-year-benefits-organizers-as-well-as-larger-research-community\/","title":{"rendered":"MineRL sample-efficient reinforcement learning challenge\u2014back for a second year\u2014benefits organizers, as well as larger research community"},"content":{"rendered":"\n
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To unearth a diamond in the block-based open world of Minecraft requires the acquisition of materials and the construction of tools before any diamond mining can even begin. Players need to gather wood, which they\u2019ll use to make a wood pickaxe for mining stone underground. They\u2019ll use the stone to fashion a stone pickaxe and, with the tool upgrade, mine iron ore. They\u2019ll build a furnace for smelting the iron and use that to make the iron pickaxe they need to start their search for the precious gem. Each task results in a stronger tool and brings players closer to retrieving that coveted diamond. The efforts to organize competitions designed to advance the state of the art feel quite similar. In fact, the research process in general feels quite similar. As you gain more knowledge and experience, forge new and deeper collaborations, and leverage and improve resources\u2014collectively, stronger tools<\/em>\u2014uncovering a gem or many of them in the form of breakthroughs and promising new directions to explore becomes more reachable.<\/p>\n\n\n\n

After none of the submitted agents were able to obtain a diamond in Minecraft during last year\u2019s MineRL competition<\/a>, the sample-efficient reinforcement learning challenge is back and even better thanks to an additional dataset, structural changes that we see contributing to a more robust and wider-appealing contest, and the addition of DeepMind and OpenAI to the organizing team. MineRL 2020 (opens in new tab)<\/span><\/a> is the fourth competition based on Project Malmo<\/a>, an experimentation platform using Minecraft to advance AI. MineRL, the brainchild of a team of researchers from Carnegie Mellon University, tackles an ambitious problem facing the machine learning community: an increasing demand for large amounts of computational resources to replicate state-of-the-art research. Solving this challenge is key to making AI more accessible. To encourage the kind of efficiency in the RL space that will help make that possible, MineRL participants are limited in the amount of data they can use and time they can spend training an agent to complete the competition task of mining a diamond\u2014no more than 8 million samples over four days or less using a single GPU machine.<\/p>\n\n\n\n\t

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On Second Thought<\/h2>\n\t\t\t\t\n\t\t\t\t\t\t\t\t

A video series with Sinead Bovell built around the questions everyone\u2019s asking about AI. With expert voices from across Microsoft, we break down the tension and promise of this rapidly changing technology, exploring what\u2019s evolving and what\u2019s possible.<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t

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MineRL 2020, hosted and supported again by the competition platform AIcrowd, is part of the competition track at this year\u2019s Conference on Neural Information Processing Systems (NeurIPS 2020 (opens in new tab)<\/span><\/a>). Last year, the competition was also included in the conference lineup. Over 1,000 participants registered, and more than 50 people attended the affiliated NeurIPS workshop, during which the top teams presented their creative approaches. Microsoft is delighted to once again be among the organizers of a competition that is truly a result of great teamwork.<\/p>\n\n\n\n

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