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Hierarchical reinforcement learning boosts air defense efficiency

Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.
Nature

Multi-timescale reinforcement learning in the brain

Many of the recent advances in artificial intelligence rely on temporal difference (TD) reinforcement learning (RL) in which the TD learning rule is used to learn predictive information 1 (equation (2 ...
Nature

Competitive swarm reinforcement learning improves stability and performance of deep reinforcement learning

Reinforcement Learning (RL) enable agents to learn from interactions with their environment by mapping environmental states to actions, aiming to maximize the value of received feedback signals. The ...
EurekAlert!

A graph reinforcement learning framework for real-time distributed multi-robot task allocation

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
techtimes

Open-Source Coding Model Ornith-1.0 Writes Its Own Training Scaffold in Reinforcement Learning

DeepReinforce today released Ornith-1.0, a family of open-source coding models built around a mechanism most RL-trained agents avoid: the model itself writes the training harness that guides its own ...