Symbolic Activities in Virtual Spaces

This paper presents an approach to combine concepts ofsymbolic acting and virtual storytelling with the support ofcooperative processes. We will motivate why symboliclanguages are relevant in the social context of awarenessapplications. We will describe different symbolicpresentations and illustrate their application in three differentprototypes

Bounded-time fault-tolerant rule-based systems

Two systems concepts are introduced: bounded response-time and self-stabilization in the context of rule-based programs. These concepts are essential for the design of rule-based programs which must be highly fault tolerant and perform in a real time environment. The mechanical analysis of programs for these two properties is discussed. The techniques are used to analyze a NASA application

Content repositories and social networking : can there be synergies?

This paper details the novel application of Web 2.0 concepts to current services offered to Social Scientists by the ReDReSS project, carried out by the Centre for e-Science at Lancaster University. We detail plans to introduce Social Bookmarking and Social Networking concepts into the repository software developed by the project. This will result in the improved discovery of e-Science concepts and training to Social Scientists and allow for much improved linking of resources in the repository. We describe plans that use Social Networking and Social Bookmarking concepts, using Open Standards, which will promote collaboration between researchers by using information gathered on user’s use of the repository and information about the user. This will spark collaborations that would not normally be possible in the academic repository context

A Non Monotonic Reasoning framework for Goal-Oriented Knowledge Adaptation

In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of our application of this logic, the overall pipeline of our system works as follows: given a goal expressed as a set of properties, if the knowledge base does not contain a concept able to fulfill all these properties, then our system looks for two concepts to recombine in order to extend the original knowledge based satisfy the goal

Towards Context Driven Modularization of Large Biomedical Ontologies

Formal knowledge about human anatomy, radiology or diseases is necessary to support clinical applications such as medical image search. This machine processable knowledge can be acquired from biomedical domain ontologies, which however, are typically very large and complex models. Thus, their straightforward incorporation into the software applications becomes difficult. In this paper we discuss first ideas on a statistical approach for modularizing large medical ontologies and we prioritize the practical applicability aspect. The underlying assumption is that the application relevant ontology fragments, i.e. modules, can be identified by the statistical analysis of the ontology concepts in the domain corpus. Accordingly, we argue that most frequently occurring concepts in the domain corpus define the application context and can therefore potentially yield the relevant ontology modules. We illustrate our approach on an example case that involves a large ontology on human anatomy and report on our first manual experiments

Asynchronous Multi-Context Systems

In this work, we present asynchronous multi-context systems (aMCSs), which provide a framework for loosely coupling different knowledge representation formalisms that allows for online reasoning in a dynamic environment. Systems of this kind may interact with the outside world via input and output streams and may therefore react to a continuous flow of external information. In contrast to recent proposals, contexts in an aMCS communicate with each other in an asynchronous way which fits the needs of many application domains and is beneficial for scalability. The federal semantics of aMCSs renders our framework an integration approach rather than a knowledge representation formalism itself. We illustrate the introduced concepts by means of an example scenario dealing with rescue services. In addition, we compare aMCSs to reactive multi-context systems and describe how to simulate the latter with our novel approach.Comment: International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), co-located with the 21st European Conference on Artificial Intelligence (ECAI 2014). Proceedings of the International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), pages 31-37, technical report, ISSN 1430-3701, Leipzig University, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-15056

On functional module detection in metabolic networks

Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models