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A novel deep recurrent reinforcement learning framework is proposed to address the partial observability problem. The historical observation sequence, which ...
In this paper, a deep recurrent reinforcement learning (DRRL)-based guidance method is investigated to address the intercept guidance problem against ...
Jun 28, 2024 · In this paper, a deep recurrent reinforcement learning (DRRL)-based guidance method is investigated to address the intercept guidance problem ...
Different from traditional guidance laws, the proposed guidance law can avoid tedious manual settings and save cost efforts. First, the interception problem is ...
This work proposes a recorded recurrent twin delayed deep deterministic (RRTD3) policy gradient algorithm to solve the challenge of constructing guidance laws.
We present a novel guidance law that uses observations consisting solely of seeker line-of-sight angle measurements and their rate of change.
[PDF] Reinforcement Learning for Angle-Only Intercept Guidance of ...
dspace.mit.edu › 2020_scitech01
We present a novel guidance law that uses observations consisting solely of seeker line of sight angle measurements and their rate of change.
To achieve the intelligent interception of different types of maneuvering evaders, based on deep reinforcement learning, a novel intelligent differential ...
We present a novel guidance law that uses observations consisting solely of seeker line of sight angle measurements and their rate of change.
Jan 1, 2024 · During training, the hidden states of the RNN layer in the policy network are recorded to overcome the partially observable problem that this ...