Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
The problem of multi-robot patrol in adversarial environments has been gaining considerable interest during the recent years.In this problem, a team of mobile robots is required t...
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
With the increasing adoption of Java for parallel and distributed computing, there is a strong motivation for enhancing the expressive elegance of the RMI paradigm with flexible ...
Dawid Kurzyniec, Tomasz Wrzosek, Vaidy S. Sunderam...
Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement lear...
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vinc...