A Learning Algorithm for Risk-Sensitive Cost

A Learning Algorithm for Risk-Sensitive Cost

A particle swarm optimization algorithm for minimization analysis of cost-sensitive attack graphs

To prevent an exploit, the security analyst must implement a suitable countermeasure. In this paper, we consider cost-sensitive attack graphs (CAGs) for network vulnerability analysis. In these attack graphs, a weight is assigned to each countermeasure to represent the cost of its implementation. There may be multiple countermeasures with different weights for preventing a single exploit. Also,...

A Cost-Sensitive Learning Algorithm for Fuzzy Rule-Based Classifiers

Designing classifiers may follow different goals. Which goal to prefer among others depends on the given cost situation and the class distribution. For example, a classifier designed for best accuracy in terms of misclassifications may fail when the cost of misclassification of one class is much higher than that of the other. This paper presents a decision-theoretic extension to make fuzzy rule...

An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learning

Cost-Sensitive Reinforcement Learning

We introduce cost-sensitive regression as a way to introduce information obtained by planning as background knowledge into a relational reinforcement learning algorithm. By offering a trade-off between using knowledge rich, but computationally expensive knowledge resulting from planning like approaches such as minimax search and computationally cheap, but possibly incorrect generalizations, the...