Catálogo de publicaciones - libros

We introduce a novel stochastic local search algorithm for the vertex cover problem. Compared to current exhaustive search techniques, our algorithm achieves excellent performance on a suite of problems drawn from the field of biology. We also evaluate our performance on the commonly used DIMACS benchmarks for the related clique problem, finding that our approach is competitive with the current best stochastic local search algorithm for finding cliques. On three very large problem instances, our algorithm establishes new records in solution quality.

The Brio labyrinth, is a popular game consisting of a board with holes and walls. In addition, the game has knobs which are used to tip the board in two planar directions for controlling the angle of the board. The aim of the game is to maneuver a steel ball along a marked path from a starting position to a final position on the board by tipping it so that the ball moves without falling into any of the holes. The path is partially bordered by the walls. Some of the walls form corners, where the ball can be controlled easily.

Artificial Intelligence (AI) and Cognitive Psychology (CP) are two sciences of intelligent systems that share many features. If we want, nevertheless, to contrast AI with CP, we must investigate differences between the strategies they follow in exploring intelligence. To do so, I transform the Turing Test into a more adequate intelligence test based on a necessary condition for intelligence, namely that intensions of second-order intentional predicates are observable in a system (sect. 2). I then contrast CP and AI by their criteria for progress in research on this necessary condition for intelligence (sect. 3).

MEGA [7], a mathematical assistant environment comprising an interactive proof assistant, a proof planner, a structured knowledge base, a graphical user interface, access to external reasoners, etc., is being developed since the early 90’s at Saarland University. Similar to HOL4, Isabelle/HOL, Coq, or Mizar, the overall goal of the project is to develop a system platform for formal methods (not only) in mathematics and computer science. In MEGA, user and system interact in order to produce verifiable and trusted proofs. By continously improving (not only) automation and interaction support in the system we want to ease the usually very tedious formalization and proving task for the user.

Selecting and initiating an appropriate (possibly cooperative) behavior in a given context is one of the most important and difficult tasks for soccer playing robots or software agents. Of course, this applies to other complex robot environments as well.

In this paper we present a methodology for using Case Based Reasoning techniques for this challenging problem. We will show a complete workflow from case-acquisition up to case-base maintenance. Our system uses several techniques for optimizing the case base and the retrieval step in order to be efficient enough to use it in a realtime environment.

The framework we propose could successfully be tested within the robot soccer domain where it was able to select and initiate complex game plays by using experience from previous situations. Due to space constraints we can give just a very brief overview about the most important aspects of our system here.

Multiple sequence alignment (MSA) is a problem in computational biology with the goal to discover similarities between DNA or protein sequences. One problem in larger instances is that the search exhausts main memory. This paper applies disk-based heuristic search to solve MSA benchmarks. We extend iterative-deepening dynamic programming, a hybrid of dynamic programming and IDA*, for which optimal alignments with respect to similarity metrics and affine gap cost are computed. We achieve considerable savings of main memory with an acceptable time overhead. By scaling buffer sizes, the space-time trade-off can be adapted to existing resources.

This paper presents the text generation module of , a multimodal dialogue system. The generation module bases on NipsGen which combines SPIN, originally a parser developed for spoken language, and a tree-adjoining grammar framework for German. NipsGen allows to mix full generation with canned text.

Load forecasting allows electric utilities to enhance energy purchasing and generation, load switching, contracts negotiation and infrastructure development [1].

In this paper, we present a system for simultaneous localization and map building of a mobile robot, based on an attentional landmark detector. A biologically motivated attention system finds regions of interest which serve as visual landmarks for the robot. The regions are tracked and matched over consecutive frames to build stable landmarks and to estimate the 3D position of the landmarks in the environment. Furthermore, matching of current landmarks to database entries enables loop closing and global localization. Additionally, the system is equipped with an active camera control, which supports the system with a tracking, a re-detection, and an exploration behaviour.

To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests.