Exploring Reinforcement Learning: Can AI Learn to Play QWOP? | Digi-Key Electronics

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  • Опубликовано: 1 фев 2025

Комментарии • 10

  • @Dinkleberg96
    @Dinkleberg96 Год назад +3

    This is really interesting. I would love to learn more about A.I. I'm definitely staying tunned for the next episode! Amazing work as always Mr. Hymel!

  • @BeckyStern
    @BeckyStern Год назад +2

    Thank you Shawn!!! This is awesome. Unlike my QWOP skills. 😆

  • @t.vigneshnayak7886
    @t.vigneshnayak7886 Год назад +2

    we need ai related series, please bring more videos.

  • @Moodie111
    @Moodie111 Год назад

    A few things need to be added. First: the goal shouldn't just be covering the most distance, it should be covering the most distance in the least time. The video shows the runner essentially hopping on one foot. Imposing a fastest time goal would promote faster solutions using both legs. Second: code should be added to disallow sequential steps using the same foot, so that the only gait allowed would be left-right-left-right-left-right. These would be major improvements.

  • @JSStrom
    @JSStrom Год назад +1

    That was very interesting indeed...
    Best

  • @michaelnilan7413
    @michaelnilan7413 Год назад +1

    Great content 😍🤩

  • @kalvincochran9505
    @kalvincochran9505 Год назад

    It’s not cheating it’s just a phenomenal idea. If you would have done that it probably would have worked better