Abstract: In recent years, reinforcement learning (RL) has made great achievements in artificial intelligence. Proximal policy optimization (PPO) is a representative RL algorithm, which limits the ...
Abstract: Multi-UAV assisted data collection has been widely applied to enhance data freshness in wireless sensor networks. Most existing studies focus on minimizing the maximum or average Age of ...
Discover what agentic AI is and how AI agents work. Uncover the types of agentic AI systems, their enterprise use cases, ...
Also a "backronym" for former Major Leaguer Bill Pecota, PECOTA is Baseball Prospectus' system for projecting player performance. The acronym stands for "Player Empirical Comparison and Optimization ...
In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...
The instinct is to point AI at low-stakes busywork. The bigger payoff is the high-stakes work everyone’s avoiding. Why don’t ...
连续动作空间的 PPO 算法实现 多智能体环境支持 10 种训练技巧优化 TensorBoard 训练可视化 自定义 MPE 环境（多无人机 ...
Modify the parameters in config.conf as you like.
Motivated by this, we propose a new method to train adversarial agents. Technically speaking, our approach extends the Proximal Policy Optimization (PPO) algorithm and then utilizes an explainable AI ...
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