Learning-Based Multi-UAV Flocking Control With Limited Visual Field and Instinctive Repulsion

This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...

Group-Based Distributed Auction Algorithms for Multi-Robot Task Assignment

This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a...

A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory

In recent years, frequent large-scale power grid accidents have caused serious economic losses and bad social impact, which has drawn great attention from power grid enterprises. As one of the key elements of production, safety investment plays an important role in improving the safety level and reducing accident loss. In this paper, System...