In typical real-time strategy (RTS) games, enemy units are visible only when they are within sight range of a friendly unit. Knowledge of an opponent’s disposition is limited to what can be observed through scouting. Information is costly, since units dedicated to scouting are unavailable for other purposes, and the enemy will resist scouting attempts. It is important to infer as much as possib...

We extend a series of multivariate Bayesian two-dimensional (2-D) contextual classifiers to three-dimensional (3-D) by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its six nearest 3-D neighbors.

Feature selection is a pre-processing technique used for eliminating the irrelevant and redundant features which results in enhancing the performance of the classifiers. When a dataset contains more irrelevant and redundant features, it fails to increase the accuracy and also reduces the performance of the classifiers. To avoid them, this paper presents a new hybrid feature selection method usi...

In this paper we present a new Bayesian net­ work model for classification that combines the naive Bayes (NB} classifier and the fi­ nite mixture (FM} classifier. The resulting classifier aims at relaxing the strong assump­ tions on which the two component models are based, in an attempt to improve on their classification performance, both in terms of accuracy and in terms of calibration of the...

A robust authentication system for handwritten document images carries considerable importance. The authenticity of legal documents, such as wills, signatures, etc., needs to be verified, in order to prevent fraudulent acts. The characteristics of writing style vary from person to person; by analyzing the local features of handwriting, we can possibly identify the writer. In this paper, we intr...

This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given a configuration of the discrete parents. We assume parameter independence and complete data. Further, t...

The paper presents an approach to joint tracking and classification based on belief functions as understood in the transferable belief model (TBM). The TBM model is identical to the classical model except all probability functions are replaced by belief functions, which are more flexible for representing uncertainty. It is felt that the tracking phase is well handled by the classical Kalman fil...

The simple Bayesian classi er (SBC), sometimes called Naive-Bayes, is built based on a conditional independence model of each attribute given the class. The model was previously shown to be surprisingly robust to obvious violations of this independence assumption, yielding accurate classi cation models even when there are clear conditional dependencies. The SBC can serve as an excellent tool fo...

Approaches for measuring interaction in shared workspaces mostly take on a simplistic perspective in regarding every action also as an interaction. In contrast, this paper argues that actions in shared workspace differ in their degrees of interaction and defines formal indicators for the automatic evaluation. The approach presented in this paper is based on a hybrid model that uses plan recogni...