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...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
Few attempts have been made to investigate the utility of temporal reasoning within machine learning frameworks for temporal relation classification between events in news articl...
— The application of Qualitative Reasoning to Learning Algorithms can provide these models with the capability of automate common-sense and expert reasoning. Learning algorithms ...
We present a new active learning approach to incorporate
human feedback for on-line unusual event detection. In contrast to most
existing unsupervised methods that perform passiv...