2018 (vol. 28) - Number 2

*E. Roszkowska:*

Hybrid motion control for multiple mobile robot systems

*C. Civelek:*

Stability analysis of engineering/physical dynamic systems using residual energy function

*M. Ziolko, M. Nowak:*

Design of transmultiplexer integer filters

*S. Vaidyanathan, S. Jafari, V.-T. Pham, A.T. Azar:*

A 4-D chaotic hyperjerk system with a hidden attractor, adaptive backstepping control and circuit design

*T. Kaczorek:*

An extension of Klamka's method to positive descriptor discrete-time linear systems with bounded inputs

*A. Ratajczak:*

Motion planning for nonholonomic systems with earlier destination reaching

*K.C. Patra, B.K. Dakua:*

Investigation of limit cycles and signal stabilization of two dimensional systems with memory type nonlinear elements

ACS Abstract:

**2006 (Volume 16)**

Number 2

**Principles of constraint systems and constraint solvers**

Thom Frühwirth(Faculty of Computer Science, University of Ulm, Germany) | Slim Abdennadher(Department of Computer Science, German University Cairo, Egypt) |

**keywords:** computational logic, executable specifications, rule-based programming, program analysis, algorithms

**An introduction to interval-based constraint processing**

Gerrit Renker, Hatem Ahriz(School of Computing, The Robert Gordon University, Aberdeen, UK) |

Constraint programming is often associated with solving problems over finite domains. Many applications in engineering, cad and design, however, require solving problems over continuous (real-valued) domains. While simple constraint solvers can solve linear constraints with the inaccuracy of floating-point arithmetic, methods based on interval arithmetic allow exact (interval) solutions over a much wider range of problems. Applications of interval-based programming extend the range of solvable problems from non-linear polynomials up to those involving ordinary differential equations.

In this text, we give an introduction to current approaches, methods and implementations of interval-based constraint programming and solving. Special care is taken to provide a uniform and consistent notation, since the literature in this field employs many seemingly different, but yet conceptually related, notations and terminology.

**keywords:** constraint programming, interval-based computation, interval consistency techniques

**Filtering algorithms for the Same and UsedBy constraints**

Nicolas Beldiceanu(Ecole des Mines de Nantes, Nantes Cedex, France) | Irit Katriel, Sven Thiel(Max-Planck-Institut fur Informatik, Saarbrucken, Germany) |

*X*and

*Z*such that

*|X| > |Z|*and assigns values to them such that the multiset of values assigned to the variables in

*Z*is contained in the multiset of values assigned to the variables in

*X*. Same is the special case of UsedBy in which

*|X|=|Z|*. We show algorithms that achieve arc-consistency and bound-consistency for these constraints.

**keywords:** arc-consistency, bound-consistency, constraint programming, filtering algorithm, global constraint, network flow, strongly connected component

**Message delay and asynchronous DisCSP search**

Roie Zivan, Amnon Meisels(Department of Computer Science, Ben-Gurion University of the Negev, Israel) |

**keywords:** distributed constraint satisfaction, search, distributed AI

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