Reinforced Machine Game(@rforcedmachine) 's Twitter Profile Photo

I was asked about how we intend to use AI / Machine Learning in the game. 🤖🤔

Here's a video of the training environment and a summary of what we are building.

🧵1/6 👇

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Fabio Nogales(@fabionogales95) 's Twitter Profile Photo

🤖 Se utilizará aprendizaje por refuerzo, la IA trabajará con IA entrenándose mutuamente y esto aumentará el tamaño del modelo y datos. Para ello, se presenta una GPU NVIDIA muy grande. 🧠

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Tanat Tonguthaisri(@gastronomy) 's Twitter Profile Photo

🚀 Exciting news! Our latest research explores deep reinforcement learning for modelling protein complexes, proposing the innovative GAPN framework to tackle complex challenges. Read more at: bit.ly/3WqI4T9

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Davide Scaramuzza(@davsca1) 's Twitter Profile Photo

Check out our paper 'Actor-Critic Model Predictive Control.' Model-free (RL) is known for its strong task performance and flexibility in optimizing general reward formulations. On the other hand, (MPC) benefits from…

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T.Yamazaki(@ZappyZappy7) 's Twitter Profile Photo

AIを搭載した人型ロボットが複雑な作業をスムーズにこなす
この手先の器用さは、台所での素晴らしいヘルパーになるかもしれない
lnkd.in/gzy8rGSH

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Antonio(@manjavacas_) 's Twitter Profile Photo

has been a great experience!

I was able to talk about my research at IFMIF-DONES and learn more about autonomous accelerators.

Congratulations to the organisers and long live to ! 🤖❤️

#RL4AA24 has been a great experience!

I was able to talk about my research at @IFMIF_DONES and learn more about autonomous accelerators.

Congratulations to the organisers and long live to #ReinforcementLearning! 🤖❤️
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Miruna Pîslar(@Miruna_Pislar) 's Twitter Profile Photo

Mode-switching policies offer amazing flexibility in !🤖Loren Anderson's blog post provides a great analysis, building on our 'When should agents explore?' paper. See what makes these policies so adaptable:
iclr-blogposts.github.io/2024/blog/mode…
Thank you, Loren!

Mode-switching policies offer amazing flexibility in #ReinforcementLearning!🤖Loren Anderson's #ICLR2024 blog post provides a great analysis, building on our 'When should agents explore?' paper. See what makes these policies so adaptable:
iclr-blogposts.github.io/2024/blog/mode…
Thank you, Loren!
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nguyen sao mai @ ICLR2024(@nguyensmai) 's Twitter Profile Photo

A symbolic representation of tasks is key for compositionality. Our goal-conditioned hierarchical algo STAR learns online a discrete representation of continuous sensorimotor space
👉openreview.net/pdf?id=odY3PkI…

A symbolic representation of tasks is key for compositionality. Our goal-conditioned hierarchical #ReinforcementLearning algo STAR learns online a discrete representation of continuous sensorimotor space #ReachabilityAnalysis #ContinualLearning #ICLR2024
👉openreview.net/pdf?id=odY3PkI…
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