Results 1  10
of
61
The Farthest Color Voronoi Diagram and Related Problems (Extended Abstract)
 Abstracts 17th European Workshop Comput. Geom. CG 2001, Freie Universität
, 2001
"... Manuel Abellanas # Ferran Hurtado ## Christian Icking ** * Rolf Klein ** ** Elmar Langetepe ** ** Lihong Ma ** ** Belen Palop ** * ** Vera Sacristan ## Suppose there are k types of facilities, e. g. schools, post o#ces, supermarkets, modeled by n colored points in the plane, each type ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
Manuel Abellanas # Ferran Hurtado ## Christian Icking ** * Rolf Klein ** ** Elmar Langetepe ** ** Lihong Ma ** ** Belen Palop ** * ** Vera Sacristan ## Suppose there are k types of facilities, e. g. schools, post o#ces, supermarkets, modeled by n colored points in the plane, each type
The Pledge Algorithm Reconsidered under Errors in Sensors and Motion
 In Proc. of the 1th Workshop on Approximation and Online Algorithms
, 2004
"... We consider the problem of escaping from an unknown polygonal maze under limited resources and under errors in sensors and motion. ..."
Abstract

Cited by 4 (4 self)
 Add to MetaCart
We consider the problem of escaping from an unknown polygonal maze under limited resources and under errors in sensors and motion.
Searching for the Kernel of a Polygon: A Competitive Strategy Using SelfApproaching Curves
 In Proc. 11th Annu. ACM Sympos. Comput. Geom
, 1995
"... We present a competitive strategy for walking into the kernel of an initially unknown starshaped polygon. From an arbitrary start point, s, within the polygon, our strategy finds a path to the closest kernel point, k, whose length does not exceed 5.3331 ...times the distance from s to k. This is ..."
Abstract

Cited by 30 (12 self)
 Add to MetaCart
We present a competitive strategy for walking into the kernel of an initially unknown starshaped polygon. From an arbitrary start point, s, within the polygon, our strategy finds a path to the closest kernel point, k, whose length does not exceed 5.3331 ...times the distance from s to k. This is complemented by a general lower bound of # 2. Our analysis relies on a result about a new and interesting class of curves which are selfapproaching in the following sense.
c © 1997 Kluwer Academic Publishers. Printed in the Netherlands. A Correct Logic Programming Computation of Default Logic Extensions
, 1994
"... Abstract. We present a method of representing some classes of default theories as normal logic programs. The main point is that the standart semantics (i.e., SLDNFresolution) computes answer substitutions that correspond exactly to the extensions of the represented default theory. This means that w ..."
Abstract
 Add to MetaCart
Abstract. We present a method of representing some classes of default theories as normal logic programs. The main point is that the standart semantics (i.e., SLDNFresolution) computes answer substitutions that correspond exactly to the extensions of the represented default theory. This means that we give a correct implementation of default logic. We explain the steps of constructing a logic program LogProg(P;D) from a given default theory (P;D), give some examples, and derive soundness and completeness results. Key words: default logic, logic programming, SLDNFresolution. 1.
Exploring an Unknown Cellular Environment
 BENGURION UNIVERSITY OF THE NEGEV
, 2000
"... We investigate the exploration problem of a shortsighted mobile robot moving about in an unknown cellular room. In order to explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified ce ..."
Abstract

Cited by 11 (2 self)
 Add to MetaCart
We investigate the exploration problem of a shortsighted mobile robot moving about in an unknown cellular room. In order to explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified cell adjacent to the room's outer wall; it visits each cell, and returns to the start. Our interest is in a short exploration tour, that is, in keeping the number of multiple cell visits small. For abitrary environments containing obstacles we provide a strategy producing tours of length S # C+ 1 2 E+H 3, where C denotes the number of cellsthe area, E denotes the number of boundary edgesthe perimeter, and H is the number of obstacles.
Optimal Competitive Online Ray Search with an ErrorProne Robot
 IN ACCEPTED FOR WEA
, 2005
"... We consider the problem of finding a door along a wall with a blind robot that neither knows the distance to the door nor the direction towards of the door. This problem can be solved with the wellknown doubling strategy yielding an optimal competitive factor of 9 with the assumption that the ro ..."
Abstract

Cited by 3 (3 self)
 Add to MetaCart
We consider the problem of finding a door along a wall with a blind robot that neither knows the distance to the door nor the direction towards of the door. This problem can be solved with the wellknown doubling strategy yielding an optimal competitive factor of 9 with the assumption that the robot does not make any errors during its movements. We study the case that the robot's movement is erroneous. In this case
The Tourist in the Shopping Arcade1
"... Abstract: A tourist is searching for a gift and moves along a shopping arcade until the desired object gets into sight. The location of the corresponding shop is not known in advance. Therefore in this online setting the tourist has to make a detour in comparison to an optimal offline straight lin ..."
Abstract
 Add to MetaCart
Abstract: A tourist is searching for a gift and moves along a shopping arcade until the desired object gets into sight. The location of the corresponding shop is not known in advance. Therefore in this online setting the tourist has to make a detour in comparison to an optimal offline straight line path to the desired object. We can show that there is a strategy for the tourist, so that the path length is never greater than C ∗ times the optimal offline path length, where C ∗ = 1.059401... holds. Furthermore, there is no strategy that attains a competitive factor smaller than C∗.
Lower bounds for the polygon exploration problem
 Universidad de Sevilla
, 2004
"... We improve the best known lower bound for the polygon exploration problem from 1.2071 to 1.2825. 1 ..."
Abstract

Cited by 4 (2 self)
 Add to MetaCart
We improve the best known lower bound for the polygon exploration problem from 1.2071 to 1.2825. 1
An Optimal Competitive Strategy for Walking in Streets
 In Proc. 16th Sympos. Theoret. Aspects Comput. Sci
, 1999
"... We present an optimal strategy for searching for a goal in a street which achieves the competitive factor of # 2, thus matching the best lower bound known before. This finally settles an interesting open problem in the area of competitive path planning many authors have been working on. ..."
Abstract

Cited by 17 (8 self)
 Add to MetaCart
We present an optimal strategy for searching for a goal in a street which achieves the competitive factor of # 2, thus matching the best lower bound known before. This finally settles an interesting open problem in the area of competitive path planning many authors have been working on.
Searching a goal on m rays within a fixed distance (Extended Abstract)
"... The problem of searching a goal on m rays is well known. If the goal is in unknown position then the target can be found by choosing a path not longer than 1+2m # m m1 # m1 times the distance from the origin to the target. It was already shown that this competitive ratio is optimal. We investigate ..."
Abstract
 Add to MetaCart
The problem of searching a goal on m rays is well known. If the goal is in unknown position then the target can be found by choosing a path not longer than 1+2m # m m1 # m1 times the distance from the origin to the target. It was already shown that this competitive ratio is optimal. We investigate the case where the target is known to be within a fixed distance, r, of the start point, and determine the optimum competitive factor, C(r) < 1+2m # m m1 # m1 , that can be achieved by a competitive strategy S(r), under this additional assumption.
Results 1  10
of
61