Frank Dylla

Qualitative spatial representation and reasoning in the SparQ-toolbox

A multitude of calculi for qualitative spatial reasoning (QSR) have been proposed during the last two decades. The number of practical applications that make use of QSR techniques is, however, comparatively small. One reason for this may be seen in the difficulty for people from outside the field to incorporate the required reasoning techniques into their software. Sometimes, proposed calculi are only partially specified and implementations are rarely available. With the SparQ toolbox presented in this text, we seek to improve this situation by making common calculi and standard reasoning techniques accessible in a way that allows for easy integration into applications. We hope to turn this into a community effort and encourage researchers to incorporate their calculi into SparQ. This text is intended to present SparQ to potential users and contributors and to provide an overview on its features and utilization.

Spatio-terminological inference for the design of ambient environments

We present an approach to assist the smart environment design process by means of automated validation of work-in-progress designs. The approach facilitates validation of not only the purely structural requirements, but also the functional requirements expected of a smart environment whilst keeping in mind the plethora of sensory and interactive devices embedded within such an environment. The approach, founded in spatio-terminological reasoning, is illustrated in the context of formal ontology modeling constructs and reasoners, industrial architecture data standards and state-of-the-art commercial design software.

Exploiting qualitative spatial neighborhoods in the situation calculus

We present first ideas on how results about qualitative spatial reasoning can be exploited in reasoning about action and change. Current work concentrates on a line segment based calculus, the dipole calculus and necessary extensions for representing navigational concepts like turn right. We investigate how its conceptual neighborhood structure can be applied in the situation calculus for reasoning qualitatively about relative positions in dynamic environments.

Qualitative Spatial Reasoning with Conceptual Neighborhoods for Agent Control

Research on qualitative spatial reasoning has produced a variety of calculi for reasoning about orientation or direction relations. Such qualitative abstractions are very helpful for agent control and communication between robots and humans. Conceptual neighborhood has been introduced as a means of describing possible changes of spatial relations which e.g. allows action planning at a high level of abstraction. We discuss how the concrete neighborhood structure depends on application-specific parameters and derive corresponding neighborhood structures for the

Towards a league-independent qualitative soccer theory for robocup

\mathcal{OPRA}_m

Approaching A Formal Soccer Theory FromBehaviour Specifi Cations In Robotic Soccer

calculus. We demonstrate that conceptual neighborhoods allow resolution of conflicting information by model-based relaxation of spatial constraints. In addition, we address the problem of automatically deriving neighborhood structures and show how this can be achieved if the relations of a calculus can be modeled in another calculus for which the neighborhood structure is known.

Algebraic Properties of Qualitative Spatio-temporal Calculi

The paper discusses a top-down approach to model soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple RoboCup soccer leagues, i.e. for different hardware platforms. We investigate if and how soccer theory can be formalized such that specification and execution is possible. The advantage is clear: theory abstracts from hardware and from specific situations in leagues. We introduce basic primitives compliant with the terminology known in soccer theory, discuss an example on an abstract level and formalize it. We then consider aspects of different RoboCup leagues in a case study and examine how examples can be instantiated in three different leagues.

Interleaved inductive-abductive reasoning for learning complex event models

This chapter discusses a top-down approach to modelling soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple robotic soccer leagues in the RoboCup. We investigate if and how soccer theory can be formalized such that specifi cation and execution are possible. The advantage is clear: theory abstracts from hardware and from specifi c situations in different leagues. We introduce basic primitives compliant with the terminology known in soccer theory, discuss an example on an abstract level and formalize it. The formalization of soccer presented here is appealing. It goes beyond the behaviour specifi cation of soccer playing robots. For sports science a unifi ed formal soccer theory might help to better understand and to formulate basic concepts in soccer. The possibility of the formalization to develop computer programs, which allow to simulate and to reason about soccer moves, might also take sports science a step further.

Lowering the barrier: how the what-you-see-is-what-you-map paradigm enables people to contribute volunteered geographic information

Qualitative spatial and temporal reasoning is based on so-called qualitative calculi. Algebraic properties of these calculi have several implications on reasoning algorithms. But what exactly is a qualitative calculus? And to which extent do the qualitative calculi proposed meet these demands? The literature provides various answers to the first question but only few facts about the second. In this paper we identify the minimal requirements to binary spatio-temporal calculi and we discuss the relevance of the according axioms for representation and reasoning. We also analyze existing qualitative calculi and provide a classification involving different notions of relation algebra.

On Generalizing Orientation Information in \mathcal{OPRA}_m

We propose an interleaved inductive-abductive model for reasoning about complex spatio-temporal narratives. Typed Inductive Logic Programming (Typed-ILP) is used as a basis for learning the domain theory by generalising from observation data, whereas abductive reasoning is used for noisy data correction by scenario and narrative completion thereby improving the inductive learning to get semantically meaningful event models. We apply the model to an airport domain consisting of video data for 15 turn-arounds from six cameras simultaneously monitoring logistical processes concerned with aircraft arrival, docking, departure etc and a verbs data set with 20 verbs enacted out in around 2500 vignettes. Our evaluation and demonstration focusses on the synergy afforded by the inductive-abductive cycle, whereas our proposed model provides a blue-print for interfacing common-sense reasoning about space, events and dynamic spatio-temporal phenomena with quantitative techniques in activity recognition.