Abstract: This letter applies a multiagent fuzzy Q-learning (FQL) algorithm, incorporated with a model-free nonlinear controller (MFNC), entitled FQL-MFNC for stabilized controlling of a recently ...

Extreme events such as earthquakes can readily cause structural damage and operational disturbances in power grids, thereby weakening the system’s supply stability and recovery capability and posing ...

In our framework, an RL rule is represented by a meta-network that determines the targets towards which the agent should move its predictions and policy (Fig. 1c). This allows the system to discover ...

Automated guided vehicles play a crucial role in transportation and industrial environments. This paper presents a proposed Bio Particle Swarm Optimization (BPSO) algorithm for global path planning.

These include such learning paradigms as Q-Learning and the Deep Q-Networks setups. Reinforcement Learning paradigms essentially aim at teaching robots to undertake certain actions that will be used ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Abstract: Energy storage plays a significant role in improving the stability of distributed energy, improving power quality and peak regulation in the micro-grid system, which is of great significance ...

With the development of bionic computer vision for images processing, researchers have easily obtained high-resolution zoom sensing images. The development of drones equipped with high-definition ...

Swimming microorganisms and migrating cells have developed various strategies in order to move in nutrient-rich or other chemical environments. We apply a genetic algorithm to the internal ...

Aiming at the disadvantages of the basic ant colony algorithm, this paper proposes an improved ant colony algorithm for robot global path planning. First, adjust the pheromone evaporation rate ...