2018 (vol. 28) - Number 1

*I. Duleba, I. Karcz-Duleba:*

A comparison of methods solving repeatable inverse kinematics for robot manipulators

*A. Niederliñski:*

A new approach for modelling uncertainty in expert systems knowledge bases

*T.T. Tuan, L.D. Tufa, M.I.A. Mutalib, N.M. Ramli :*

Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model

*M. Kaleta:*

Network winner determination problem

*A. Kowalewski:*

Extremal problems for parabolic systems with time-varying lags

*T. Rybus, K. Seweryn, J.Z. S±siadek:*

Application of predictive control for manipulator mounted on a satellite

*T. Kaczorek:*

Reachability and observability of positive discrete-time linear systems with integer positive and negative powers of the state Frobenius matrices

*G. Grassi, A. Ouannas, V-T. Pham:*

A general unified approach to chaos synchronization in~continuous-time systems (with or without equilibrium points) as well as in discrete-time systems

*D. Pazderski:*

A robust smooth controller for a unicycle-like robot

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

<< Back