Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
To investigate whether Natural Language feedback improves learning, we developed two different feedback generation engines, that we systematically evaluated in a three way comparis...
Barbara Di Eugenio, Davide Fossati, Dan Yu, Susan ...
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
Handling terminology is an important matter in a translation workflow. However, current Machine Translation (MT) systems do not yet propose anything proactive upon tools which ass...
Abstract— Learning techniques in robotic grasping applications have usually been concerned with the way a hand approaches to an object, or with improving the motor control of man...
Antonio Morales, Eris Chinellato, Andrew H. Fagg, ...