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
The purpose of this study is to investigate the consistency of students' behavior regarding their pace of actions over sessions within an online course. Pace in a session is d...
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a ba...
Table lookup with interpolation is used for many learning and adaptation tasks. Redundant mappings capture the important concept of \motor skill," which is important in real,...
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...