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    Team CDS wins the MineRL Challenge 2019! Congrats to Team mc_rl & Team I4DS for their ranking AI agents. Thank you to all the participants & sponsors who brought the MineRL Challenge to life. Dive into the dataset:

    A team photo of the MineRL Challenge 2019 at Neurips 2019 in Vancouver, BC.
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  2. proslijedio/la je Tweet
    26. stu 2019.

    Together with a fantastic team, led by , we’re organising the MineRL competition at . I’ve been hugely impressed by the participants’ ideas and submissions so far. If you want to learn more about the competition, check out this article - in nature news today!

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  3. proslijedio/la je Tweet
    26. stu 2019.

    Very exciting to see that the project started by my PhD student and research scientist at CMU almost 2 years ago has been featured on Nature news: Congrats!

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  4. proslijedio/la je Tweet

    Round 1 of the Obtain Diamond competition just came to a close. Very impressed with the progress of the teams! Here's the current top submission utilizing hierarchical RL and imitation learning! Stay tuned:

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  5. proslijedio/la je Tweet
    24. kol 2019.

    I'm very excited about this RL competition! Now it's figuring out how to stop the agent from cutting down the trees after it has enough wood and getting diamonds!

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  6. proslijedio/la je Tweet
    20. kol 2019.

    Finally got the agent to chop trees with behavioural cloning

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    (っ◔◡◔)っ Happy to announce that our paper 𝙈𝙞𝙣𝙚𝙍𝙇: 𝘼 𝙇𝙖𝙧𝙜𝙚-𝙎𝙘𝙖𝙡𝙚 𝘿𝙖𝙩𝙖𝙨𝙚𝙩 𝙤𝙛 𝙈𝙞𝙣𝙚𝙘𝙧𝙖𝙛𝙩 𝘿𝙚𝙢𝙤𝙣𝙨𝙩𝙧𝙖𝙩𝙞𝙤𝙣𝙨 was accepted at 2019. (w/ ) Paper: Web:

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  8. proslijedio/la je Tweet

    It's been so fun exploring Macau with ! Excited to give our talk on MineRL (w/ ) and the MineRL Competition (w/ )! Come hear about our paper this Friday 11:00 - 12:30 in RL track Reinforcement Learning 7 (2701-2702)

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  9. proslijedio/la je Tweet

    The 2019 MineRL Competition challenges YOU to develop an agent that can obtain a diamond in Minecraft using only four days of training time. Learn more about the environments and how you can participate:

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  10. proslijedio/la je Tweet

    One of the competitors wrote a great blog-post on doing reinforcement learning in Minecraft using MineRL and Malmo! Check it out :)

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  11. proslijedio/la je Tweet

    Hi Twitter! Very happy to announce an update to the 𝚖𝚒𝚗𝚎𝚛𝚕 Minecraft gym environment! (with ) Say hello to 𝚖𝚒𝚗𝚎𝚛𝚕 0.2.3. After a painstaking journey through the MC codebase, we now have 𝙚𝙣𝙫𝙞𝙧𝙤𝙣𝙢𝙚𝙣𝙩 𝙨𝙚𝙚𝙙𝙞𝙣𝙜. pip3 install --upgrade minerl

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    Hey, 𝘄𝗲 𝗷𝘂𝘀𝘁 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝚖𝚒𝚗𝚎𝚛𝚕 𝟬.𝟮.𝟬! This includes 𝙩𝙤𝙣𝙨 of fixes to the data and a data visualizer tool! Update now: 𝚙𝚒𝚙𝟹 𝚒𝚗𝚜𝚝𝚊𝚕𝚕 --𝚞𝚙𝚐𝚛𝚊𝚍𝚎 𝚖𝚒𝚗𝚎𝚛𝚕 Get new data: 𝚖𝚒𝚗𝚎𝚛𝚕.𝚍𝚊𝚝𝚊.𝚍𝚘𝚠𝚗𝚕𝚘𝚊𝚍()

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  13. proslijedio/la je Tweet
    15. srp 2019.

    Preferred Networks is proudly serving as a co-organizer of Minecraft-based MineRL competition at NeurIPS 2019 w/ , , , and more. ChainerRL-based baseline is now available. Please sign up!

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  14. proslijedio/la je Tweet
    7. srp 2019.

    "MineRL: Towards AI in Minecraft" Competition to build agent to mine diamond in Minecraft, with limited amount of training, but also with human player data.

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  15. proslijedio/la je Tweet
    30. lip 2019.

    For this summer, I am participating in the competition. Since I have games data of human players, I took the time to analyze the dataset composed of videos, json files, and others. More info in my blog post :D

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  16. proslijedio/la je Tweet

    We're expanding our support for the academic community to organize an exciting competition on Project Malmo! The : MineRL Competition, Sample-Efficient Reinforcement Learning in Minecraft led by is now open. Check it out:

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  17. proslijedio/la je Tweet

    Excited to announce our competition: The MineRL Competition for Sample-Efficient Reinforcement Learning! With and others! Participate here!

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  18. 10. svi 2012.
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