Two simple but practical production systems are modeled using Petri Nets. Petri-net models are very useful in finding semantic errors like generalization error and missing conditions. In addition, reasoning with insufficient input information is formulated to yield meaningful results. In both rule-base verification and reasoning with insufficient data, heuristic methods like backward-chained re...

Bottom-up segmentation methods merge similar neighboring regions according to a decision rule and a merging order. In this paper, we propose a contribution for each of these two points. Firstly, under statistical hypothesis of similarity, we provide an improved decision rule for region merging based on significance tests and the recent statistical inequality of McDiarmid. Secondly, we propose a...

In this paper we present a novel algorithm, named GBAP, that jointly uses automatic programming with ant colony optimization for mining classification rules. GBAP is based on a context-free grammar that properly guides the search process of valid rules. Furthermore, its most important characteristics are also discussed, such as the use of two different heuristic measures for every transition ru...

The capability of building a model that can be understood and interpreted by humans is one of the main selling points of symbolic machine learning algorithms, such as rule or decision tree learners. However, those algorithms are most often optimized w.r.t. classification accuracy, but not the understandability of the resulting model. In this paper, we focus on a particular aspect of understanda...

& This paper presents a subgroup discovery algorithm APRIORI-SD, developed by adapting association rule learning to subgroup discovery. The paper contributes to subgroup discovery, to a better understanding of the weighted covering algorithm, and the properties of the weighted relative accuracy heuristic by analyzing their performance in the ROC space. An experimental comparison with rule learn...

In this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. Two objective functions, real power loss and energy not supplied index (ENS), were utilized. Multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

Evolutionary Optimization is becoming omnipresent technique in almost every process of intelligent system design. Just to name few, engineering, control, economics and forecasting are some of the scientific fields that take advantage of an evolutionary computational process that aid in engineering systems with intelligent behavior. This special issue of Journal of Universal Computer Science is ...

The airline crew scheduling problem is the problem of assigning crew itineraries to flights. We develop a new approach for solving the problem that is based on enumerating hundreds of millions random pairings. The linear programming relaxation is solved first and then millions of columns with best reduced cost are selected for the integer program. The number of columns is further reduced by a l...

The rule labeling heuristic aims to establish confluence of (left-)linear term rewrite systems via decreasing diagrams. We present a formalization of a confluence criterion based on the interplay of relative termination and the rule labeling in the theorem prover Isabelle. Moreover, we report on the integration of this result into the certifier CeTA, facilitating the checking of confluence cert...