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

PPO（Proximal Policy Optimization） 这个后来在 RLHF 和大模型训练中被广泛使用的经典算法，当年曾被 NIPS 2017 拒之门外。 这件事最近由 PPO 作者 John Schulman 本人提起。他只用一句话概括了这段往事：PPO，曾经被 NIPS 2017 拒了。

The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...

This project implements a reinforcement learning system for robotic grasping using a 7-DOF KUKA robotic arm in a PyBullet simulation. The agent uses visual input to perform grasping tasks and is ...

The performance of the state-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep Deterministic Policy Gradient, and Soft Actor-Critic for generating a ...