Abstract: We describe and verify a convergence model that allows the islands in a parallel genetic algorithm to run at different speeds, and to simulate the effects of communication or machine failure ...

Abstract: Indoor scenarios can pose challenges for localization. Effects such as multipath and non-line-of-sight propagation between devices can cause errors in positioning systems that utilize radio ...

When your machine learning model isn't converging, it's akin to a car engine that won't start—it's frustrating and halts progress. Convergence in machine learning means that your model is ...

To address this, we propose a novel multi-agent cooperative model ... of the graph convolutional network. The results also show that the graph MADDPG with a transformer on the critic and actor ...

Subsequently, by integrating physical models and ray acoustics, relevant features of mesoscale eddies and convergence zones are extracted. Then, K-fold cross-validation and sparrow search algorithms ...

In this project, we tried to build a reinforcement learning (RL) model, which is an action-reward system which helps machines to ... Understanding and using graph structure is crucial, because even ...