In recent trends, artificial intelligence (AI) is used for the creation of complex automated
control systems. Still, researchers are trying to make a completely autonomous system that …

In recent years, the research on reinforcement learning (RL) has focused on function
approximation in learning prediction and control of Markov decision processes (MDPs). The …

The recent advances in deep neural networks have led to effective vision-based
reinforcement learning methods that have been employed to obtain human-level controllers …

Develo** an effective memetic algorithm that integrates the Particle Swarm Optimization
(PSO) algorithm and a local search method is a difficult task. The challenging issues include …

In this paper, we propose an end-to-end modular reinforcement learning architecture for a
navigation task in complex dynamic environments with rapidly moving obstacles. In this …

Artificial Intelligence (AI) has a long tradition as a scientific field, with tremendous
achievements accomplished in the decades behind us. At the same time, in the last few …

Simulated annealing (SA) was recognized as an effective local search optimizer, and it
showed a great success in many real-world optimization problems. However, it has slow …

Reinforcement Learning is one of the many machine learning paradigms. With no labelled
data, it is concerned with balancing the exploration and exploitation of an environment with …

Goal This paper presents an immersive Virtual Reality (VR) system to analyze and train
Executive Functions (EFs) of soccer players. EFs are important cognitive functions for …

Game-like programs have become increasingly popular in many software engineering
domains such as mobile apps, web applications, or programming education. However …