Hans-Dieter Burkhard

Case-Based Reasoning Technology

Extending some Concepts of CBR - Foundations of Case Retrieval Nets.- Diagnosis and Decision Support.- Intelligent Sales Support with CBR.- Textual CBR.- Using Configuration Techniques for Adaptation.- CBR Applied to Planning.- CBR for Design.- CBR for Experimental Software Engineering.- CBR for Tutoring and Help Systems.- CBR in Medicine.- Methodology for Building CBR Applications.- Related Areas.

Case Retrieval Nets: Basic Ideas and Extensions

An efficient retrieval of a relatively small number of relevant cases from a huge case base is a crucial subtask of Case-Based Reasoning. In this article, we present Case Retrieval Nets (CRNs), a memory model that has recently been developed for this task. The main idea is to apply a spreading activation process to a net-like case memory in order to retrieve cases being similar to a posed query case. We summarize the basic ideas of CRNs, suggest some useful extensions, and present some initial experimental results which suggest that CRNs can successfully handle case bases larger than considered usually in the CBR community.

Designing Agent Behavior with the Extensible Agent Behavior Specification Language XABSL

Specific behavior description languages prove to be suitable replacements to native programming language like C++ when the number and complexity of behavior patterns of an agent increases. The XML based Extensible Agent Behavior Specification Language (XABSL) also simplifies the process of specifying complex behaviors and supports the design of both very reactive and long term oriented behaviors. XABSL uses hierarchies of behavior modules called options that contain state machines for decision making. In this paper we introduce the architecture behind XABSL, the formalization of that architecture in XML and the software library XabslEngine that runs the formalized behavior on an agent platform. The GermanTeam [9] employed XABSL in the RoboCup Sony Four Legged League competitions in Fukuoka.

The road to RoboCup 2050

The ultimate goal of the RoboCup initiative is stated as follows: by mid-21st century, a team of fully autonomous humanoid robot soccer players shall win the soccer game, comply with the official rule of the FIFA, against the winner of the most recent World Cup. The authors consider this goal from the perspective of how close we are to it and what has to be done to reach it.

On the notion of similarity in case based reasoning and fuzzy theory

Notions of similarity and neighborhood play an important role in informatics. Different disciplines have developed their own treatment of related measures. We consider this problem under the viewpoint of case based reasoning and fuzzy theory. While distance and similarity can be considered to be formally equivalent, there exist some differences concerning their intuitive use which have impact on the composition of global measures from local ones.

Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains

This paper presents Objectdirected Case Retrieval Nets, a memory model developed for an application of Case-Based Reasoning to the task of technical diagnosis. The key idea is to store cases, i.e. observed symptoms and diagnoses, in a network and to enhance this network with an object model encoding knowledge about the devices in the application domain.

CBR for Document Retrieval: The FALLQ Project

This paper reports about a project on document retrieval in an industrial setting. The objective is to provide a tool that helps finding documents related to a given query, such as answers in Frequently Asked Questions databases. A CBR approach has been used to develop a running prototypical system which is currently under practical evaluation.

Multi Robot Object Tracking and Self Localization Using Visual Percept Relations

In this paper we present a novel approach to estimating the position of objects tracked by a team of mobile robots and to use these objects for a better self localization. Modeling of moving objects is commonly done in a robo-centric coordinate frame because this information is sufficient for most low level robot control and it is independent of the quality of the current robot localization. For multiple robots to cooperate and share information, though, they need to agree on a global, allocentric frame of reference. When transforming the egocentric object model into a global one, it inherits the localization error of the robot in addition to the error associated with the egocentric model. We propose using the relation of objects detected in camera images to other objects in the same camera image as a basis for estimating the position of the object in a global coordinate system. The spatial relation of objects with respect to stationary objects (e.g., landmarks) offers several advantages: a) Errors in feature detection are correlated and not assumed independent. Furthermore, the error of relative positions of objects within a single camera frame is comparably small, b) The information is independent of robot localization and odometry. c) As a consequence of the above, it provides a highly efficient method for communicating information about a tracked object and communication can be asynchronous, d) As the modeled object is independent from robo-centric coordinates, its position can be used for self localization of the observing robot. We present experimental evidence that shows how two robots are able to infer the position of an object within a global frame of reference, even though they are not localized themselves and then use this object information for self- localization

AT Humboldt - Development, Practice and Theory

This article covers three basics of our virtual soccer team AT Humboldt: We describe our development process in the frame of a practical exercise for students. The resulting efficient agent-oriented realization is explained, and we give a theoretical embedding of our planning component based on BDI.

RoboCup: 10 Years of Achievements and Future Challenges

Will we see autonomous humanoid robots that play (and win) soccer against the human soccer world champion in the year 2050? This question is not easy to answer, and the idea is quite visionary. However, this is the goal of the RoboCup Federation. There are serious research questions that have to be tackled behind the scenes of a soccer game: perception, decision making, action selection, hardware design, materials, energy, and more. RoboCup is also about the nature of intelligence, and playing soccer acts as a performance measure of systems that contain artificial intelligence -- in much the same way chess has been used over the last century. This article outlines the current situation following 10 years of research with reference to the results of the 2006 World Championship in Bremen, Germany, and discusses future challenges.