Russel Greiner

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Smart decision making at the tactical level is important for Artificial Intelligence (AI) agents to perform well in the domain of real-time strategy (RTS) games. This paper presents a Bayesian model that can be used to predict the outcomes of isolated battles, as well as predict what units are needed to defeat a given army. Model parameters are learned from(More)
Motivation: Modern sequencing technology now permits the sequencing of entire genomes, leading to thousands of new gene sequences in need of detailed annotation. It is too time consuming to predict the properties of each protein sequence manually and to organize the results of many prediction tools by hand. The prediction process must be automated so the(More)
This is a pre-print version of a manuscript that has been submitted to a refereed venue. Abstract Naïve Bayes (NB) classifiers are popular tools for predicting the labels of query instances, after being constructed from a training set. However, many training sets contain noisy data, so a user may be reluctant to blindly trust an NB classifier. TCXplain is a(More)
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