This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Ontology learning is an important task in Artificial Intelligence, Semantic Web and Text Mining. This paper presents a novel framework for, and solutions to, three practical probl...
Rival Penalized Competitive Learning (RPCL) and its variants can perform clustering analysis efficiently with the ability of selecting the cluster number automatically. Although t...
Tao Li, Wenjiang Pei, Shao-ping Wang, Yiu-ming Che...
This paper presents a semantic-aware classification algorithm that can leverage the interoperability among semantically heterogeneous learning object repositories using different ...
Ming-Che Lee, Kun Hua Tsai, Tung Cheng Hsieh, Ti K...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...