Functional Distributed Constraint Optimization Problems (F-DCOPs) is a constraint processing framework for continuous variables in multi-agent system modeling. In the past years, researchers have proposed many F-DCOP solving algorithms with …

The key contribution of this paper is a theoretical framework to analyse humans’ decision-making strategies under uncertainty, and more specifically how human subjects manage the trade-off between information gathering (exploration) and reward …

Rational verification refers to the problem of checking which temporal logic properties hold of a concurrent/multiagent system, under the assumption that agents in the system choose strategies that form a game theoretic equilibrium. Rational …

In most urban cities, the correct design of the bus routes network is a critical task to design a successful transportation system. Thus, network designers rely on solving the Urban Transit Routing Problem (UTRP) to find a set of bus routes that …

In this paper, we investigate the properties of cutting plane based refutations for a class of integer programs called Horn constraint systems (HCSs). Briefly, a system of linear inequalities A ⋅x ≥b is called a Horn constraint system, if each …

Human Learning Optimization (HLO) is a simple yet efficient binary meta-heuristic, in which three learning operators, i.e. the random learning operator (RLO), individual learning operator (ILO) and social learning operator (SLO), are developed to …

Algorithms must often be tailored to a specific architecture and application in order to fully harness the capabilities of sophisticated computer architectures and computational implementations. However, the relationship between tuning parameters …

This paper extends Semiotic-Conceptual Analysis (SCA) to provide a means for comparing and evaluating semiotic relations (i.e. sets of signs) with respect to their ability of and efficiency of expressing conceptual structures. One contributing …

In this paper we investigate, from a graph theoretical point of view, the notion of acceptability in Dung semantics for abstract argumentation frameworks. We advance the state of the art by introducing and analyzing combinatorial structures …

In this paper, we present a set of algorithms to display a Hasse diagram of triadic concepts in Triadic Concept Analysis and compute triadic generators and association rules, including implications without any need for a preprocessing step to …

A fundamental task in formal concept analysis is the enumeration of formal concepts. Among the fastest algorithms for this task belong algorithms which are based on Close-by-One (CbO), a tree recursive algorithm using lexicographical order of …

The Universum provides prior knowledge about data in the mathematical problem to improve the generalization performance of the classifiers. Several works have shown that the Universum twin support vector machine ( U $ \mathfrak {U} $ -TSVM) is an …

In this paper we consider two closely related problems of selecting a diverse subset of points with respect to squared Euclidean distance. Given a set of points in Euclidean space, the first problem is to find a subset of a specified size M …

We briefly review properties of explainable AI proposed by various researchers. We take a structural approach to the problem of explainable AI, examine the feasibility of these aspects and extend them where appropriate. Afterwards, we review …

Bio-inspired optimization aims at adapting observed natural behavioral patterns and social phenomena towards efficiently solving complex optimization problems, and is nowadays gaining much attention. However, researchers recently highlighted an …

The support vector classification-regression machine for K-class classification (K-SVCR) is a novel multi-class classification method based on the “1-versus-1-versus-rest” structure. In this paper, we propose a least squares version of K-SVCR …

Cross-dockingis a useful concept used by many companies to control the product flow. It enables the transshipment process of products from suppliers to customers. This research thus extends the benefit of cross-docking with reverse logistics …

Density Based Clustering (DBC) methods are capable of identifying arbitrary shaped data clusters in the presence of noise. DBC methods are based on the notion of local neighborhood density estimation. A major drawback of DBC methods is their poor …

Aiming to meet increasing energy demand and reduce carbon emissions caused by fossil fuel consumption, China is vigorously supporting the diffusion of photovoltaic (PV) generation equipment. The government and banks are recognized as playing …