Nathan Lichtlé @nathanlichtle
PhD @UCBerkeley (@berkeley_ai) nathanlichtle.com Paris Joined May 2019-
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Nathan Lichtlé retweeted
New Blog Post: Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment bair.berkeley.edu/blog/2025/03/2…
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Nathan Lichtlé retweeted
This paper has everything: large-scale empirical testing, new benchmarks, and subsequent empirical recommendations that we think might make solving imperfect information games a little easier
This paper has everything: large-scale empirical testing, new benchmarks, and subsequent empirical recommendations that we think might make solving imperfect information games a little easier
Tic-Tac-Toe... but the opponent's moves are hidden. Can you outsmart our top RL agents? Play here: nathanlichtle.com/research/2p0s
Tic-Tac-Toe... but the opponent's moves are hidden. Can you outsmart our top RL agents? Play here: nathanlichtle.com/research/2p0s https://t.co/5KED6nCoD6
Nathan Lichtlé retweeted
Nathan Lichtlé retweeted
Can language models be trained to find solutions to as yet unsolved mathematical problems? The answer is yes! Check our new article 🙂 1/n
Can language models be trained to find solutions to as yet unsolved mathematical problems? The answer is yes! Check our new article 🙂 1/n
Nathan Lichtlé retweeted
We’re open-sourcing and arxiving GPUDrive, a GPU-accelerated 2.5D multi-agent driving simulator that runs at over a million FPS. Hundreds of scenes on one GPU means scalable multi-agent planning
Nathan Lichtlé retweeted
Excited to share our work about the MVT, a large-scale highway field test for which we trained autonomous vehicles to smooth out traffic flow using deep reinforcement learning, then deployed our AI controllers onto 100 vehicles in busy morning traffic. Read more below! (1/n)
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