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
This paper attempts to extend the XCS research by analyzing the impact of information exchange between XCS agents on classifier performance. Two types of information are exchange...
This article presents a 2-phase computational learning model and application. As a demonstration, a system has been built, called CHIME for Computer Human Interacting Musical Enti...
Location awareness is the key capability of mobilecomputingapplications. Despitehighdemand, indoor location technologies have not become truly ubiquitous mainly due to their requir...
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...