Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
In this paper, we proposed the learning resource ontology(LRO) models to formally describe learning content and learning context, respectively. In addition to utilizing the models...
Zongkai Yang, Tao Huang, Qingtang Liu, Xia Li, Bei...
We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industr...
Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrah...