Construction Through Decomposition: A Linear Time Algorithm for the N-queens Problem

Configuring N mutually non-attacking queens on an N-by-N chessboard is a contemporary problem that was first posed over a century ago. Over the past few decades, this problem has become important to computer scientists by serving as the standard example of backtracking search methods. A related problem, placing the N queens on a toroidal board, has been discussed in detail by Polya and Chandra, Their work focused on characterizing the solvable cases and finding regular solutions, board setups that solve the problem while arranging the queens in a regular pattern. This paper describes a new linear time divide-and-conquer algorithm that solves both problems. When applied to the toroidal problem, the algorithm yields a family of non-regular solutions based on number factorization. These solutions, in turn, can be modified to solve the standard N-queens problem for board sizes which are unsolvable on a torus

Constraint-basierte Plazierung in multimodalen Dokumenten am Beispiel desLayout-Managers in WIP

Bei innovativen intelligenten Benutzerschnittstellen, wie im Beispiel des multimodalen Präsentationssystems WIP, spielt insbesondere die automatische Plazierung von Graphiken und Texten eine wichtige Rolle. Das komplexe Plazierungsproblem läßt sich dabei als Constraint-Satisfaction-Problem auffassen. Zu dessen Lösung haben wir das System CLAY, welches ein integraler Bestandteil des Layout-Managers von WIP istentwickelt. Das Constraint-Solver-Modell CLAY, basierend auf der Kopplung zweier dedizierter Constraint-Solver, erlaubt die effiziente Verarbeitung komplexer graphischer Beziehungen, wie sie besonders im funktionalen Layout vorherrschen . CLAY stellt einen effizienten und flexiblen Mechanismus zur deklarativen Spezifikation und Lösung graphischer Gestaltungsprobleme dar . In dieser Arbeit werden dem Constraint-Solver-Modell zugrundeliegende abstrakte Algorithmen sowie den Constraint-Definitionssprachen vorgestellt und an Hand von Beispielen illustriert

An AI planning-based tool for scheduling satellite nominal operations

Satellite domains are becoming a fashionable area of research within the AI community due to the complexity of the problems that satellite domains need to solve. With the current U.S. and European focus on launching satellites for communication, broadcasting, or localization tasks, among others, the automatic control of these machines becomes an important problem. Many new techniques in both the planning and scheduling fields have been applied successfully, but still much work is left to be done for reliable autonomous architectures. The purpose of this article is to present CONSAT, a real application that plans and schedules the performance of nominal operations in four satellites during the course of a year for a commercial Spanish satellite company, HISPASAT. For this task, we have used an AI domain-independent planner that solves the planning and scheduling problems in the HISPASAT domain thanks to its capability of representing and handling continuous variables, coding functions to obtain the operators' variable values, and the use of control rules to prune the search. We also abstract the approach in order to generalize it to other domains that need an integrated approach to planning and scheduling.Publicad

Configuration control of seven degree of freedom arms

A seven-degree-of-freedom robot arm with a six-degree-of-freedom end effector is controlled by a processor employing a 6-by-7 Jacobian matrix for defining location and orientation of the end effector in terms of the rotation angles of the joints, a 1 (or more)-by-7 Jacobian matrix for defining 1 (or more) user-specified kinematic functions constraining location or movement of selected portions of the arm in terms of the joint angles, the processor combining the two Jacobian matrices to produce an augmented 7 (or more)-by-7 Jacobian matrix, the processor effecting control by computing in accordance with forward kinematics from the augmented 7-by-7 Jacobian matrix and from the seven joint angles of the arm a set of seven desired joint angles for transmittal to the joint servo loops of the arms. One of the kinematic functions constrains the orientation of the elbow plane of the arm. Another one of the kinematic functions minimizing a sum of gravitational torques on the joints. Still another one of the kinematic functions constrains the location of the arm to perform collision avoidance. Generically, one of the kinematic functions minimizes a sum of selected mechanical parameters of at least some of the joints associated with weighting coefficients which may be changed during arm movement. The mechanical parameters may be velocity errors or position errors or gravity torques associated with individual joints