The swarm robotic concept has become a topic of extensive research in hazardous environments where a fault tolerant, robust and energy efficient approach is needed. In this paper we present behavior based algorithm for target navigation and swarm distribution over hazardous targets. This work is inspired by ant colony models. Our goal is to derive a heuristic algorithm for target localization a...

Causal inference can be used to construct models that explain the performance of heuristic algorithms for NP-hard problems. In this paper, we show the application of causal inference to the algorithmic optimization process through an experimental analysis to assess the impact of the parameters that control the behavior of a heuristic algorithm. As a case study we present an analysis of the main...

Forecasting the behavior of variables (e.g., economic, financial, physical) is of strategic value for organizations, which helps to sustain practical interest in the development of alternative models and resolution procedures. This paper presents a non-linear model that combines radial basis functions and the ARMA(p,q) structure. The optimal set of parameters for such a model is difficult to fi...

The main purpose of this dissertation was to investigate the relationship between neurobiological factors and prisoners' response to a cognitive skills training program. Two research questions were formulated. The first question was as follows: What is the predictive value of neurobiological factors in relation to the outcome of a cognitive skills program for adult prisoners? Investigation of t...

The focus of this paper is the development of a computational model for intelligent agents that decides on whether to acquire required information by retrieving it from memory or by interacting with the world. First, we present a task for which such decisions have to be made. Next, we discuss an experiment that shows that humans do not apply rational expected utility analysis to make this decis...

We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification tasks. We observe a number of benefits, the most surprising of which is that a SVM trained on a wellchosen subset of the available corpus frequently performs better than one trained on all available data. The heuristic f...

This article explores three developments that arise from the fundamental theorem of Beardwood, Halton, and Hammersley on the asymptotic behavior of the shortest path through n random points. The first development concerns the role of martingales in the theory of shortest paths, especially their role in large deviation inequalities. The second development concerns the use of Lipschitz spacefilli...

Recent work aimed at developing a deeper understanding of suboptimal heuristic search has demonstrated that the use of a cost-based heuristic function in the presence of large operator cost ratio and the decision to allow re-opening of visited nodes can have a significant effect on search effort. In parallel research, phase transitions in problem solubility have proved useful in the study of pr...