Сутки из жизни G3A1SF: как я учу агента без backprop — днём он живёт, ночью учится
Что происходит с агентом, который не решает одну задачу, а живёт — долго, в мире, который всё время меняется? Я собрал NOWA-Cognitive, когнитивную а…
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RL 2: The first physical and computational RL machines(1948–1954)
Blog 1 established the rules of learning from biology. This era asked the harder question: can we build a machine that actually does it? And so, in…
RL 1: Biological foundations and the "Law of Effect" (1898– 1949)
Before GPUs. Before neural networks. Before transistors were even a rumor. There was a hungry cat in a wooden crate, trying to get to a piece of fis…
Parsewave and the Shift Toward Better Post-Training Data
With the development of AI models, it has started to occur to me that just using larger amounts of post-training data might no longer be very helpfu…
Reinforcement Learning Series
I created this series to make that steep learning curve far less daunting for you. My goal is to trace the evolution of RL chronologically—from its…
Чем запомнилась ICRA 2026: Reinforcement Learning, генерация сложных сценариев поведения и будущее робототехники
Привет, Хабр! В начале июня в Вене прошла главная международная конференция по робототехнике и автономным системам — Internation…