Nature

Novel multiagent reinforcement learning framework using twin delayed deep deterministic policy gradient for adaptive PID control in boiler turbine systems

The latest developments in industrial control applications emphasize the need for incorporating intelligent algorithms for enhanced adaptability and performance. This study addresses the challenge of ...
Aerospace and Mechanical Insider on MSN

Hierarchical reinforcement learning boosts air defense efficiency

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

Relative importance sampling for off-policy actor-critic in deep reinforcement learning

Figure 1a illustrates that off-policy learning primarily involves two policies: the behavioral policy (b), also known as the sampling distribution, and the target policy (\(\pi\)), also known as the ...