93,135 research outputs found
Answer Set Programming Modulo `Space-Time'
We present ASP Modulo `Space-Time', a declarative representational and
computational framework to perform commonsense reasoning about regions with
both spatial and temporal components. Supported are capabilities for mixed
qualitative-quantitative reasoning, consistency checking, and inferring
compositions of space-time relations; these capabilities combine and synergise
for applications in a range of AI application areas where the processing and
interpretation of spatio-temporal data is crucial. The framework and resulting
system is the only general KR-based method for declaratively reasoning about
the dynamics of `space-time' regions as first-class objects. We present an
empirical evaluation (with scalability and robustness results), and include
diverse application examples involving interpretation and control tasks
Ontology modelling methodology for temporal and interdependent applications
The increasing adoption of Semantic Web technology by several classes of applications in recent years, has made ontology engineering a crucial part of application development. Nowadays, the abundant accessibility of interdependent information from multiple resources and representing various fields such as health, transport, and banking etc., further evidence the growing need for utilising ontology for the development of Web applications. While there have been several advances in the adoption of the ontology for application development, less emphasis is being made on the modelling methodologies for representing modern-day application that are characterised by the temporal nature of the data they process, which is captured from multiple sources. Taking into account the benefits of a methodology in the system development, we propose a novel methodology for modelling ontologies representing Context-Aware Temporal and Interdependent Systems (CATIS). CATIS is an ontology development methodology for modelling temporal interdependent applications in order to achieve the desired results when modelling sophisticated applications with temporal and inter dependent attributes to suit today's application requirements
A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows
This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes.
Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques.
The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic systemā components serves as a knowledge base.
The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete.
After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system.
A real-life case (from the Kingās College hospital accident and emergency (A&E) departmentās trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling
Between Sense and Sensibility: Declarative narrativisation of mental models as a basis and benchmark for visuo-spatial cognition and computation focussed collaborative cognitive systems
What lies between `\emph{sensing}' and `\emph{sensibility}'? In other words,
what kind of cognitive processes mediate sensing capability, and the formation
of sensible impressions ---e.g., abstractions, analogies, hypotheses and theory
formation, beliefs and their revision, argument formation--- in domain-specific
problem solving, or in regular activities of everyday living, working and
simply going around in the environment? How can knowledge and reasoning about
such capabilities, as exhibited by humans in particular problem contexts, be
used as a model and benchmark for the development of collaborative cognitive
(interaction) systems concerned with human assistance, assurance, and
empowerment?
We pose these questions in the context of a range of assistive technologies
concerned with \emph{visuo-spatial perception and cognition} tasks encompassing
aspects such as commonsense, creativity, and the application of specialist
domain knowledge and problem-solving thought processes. Assistive technologies
being considered include: (a) human activity interpretation; (b) high-level
cognitive rovotics; (c) people-centred creative design in domains such as
architecture & digital media creation, and (d) qualitative analyses geographic
information systems. Computational narratives not only provide a rich cognitive
basis, but they also serve as a benchmark of functional performance in our
development of computational cognitive assistance systems. We posit that
computational narrativisation pertaining to space, actions, and change provides
a useful model of \emph{visual} and \emph{spatio-temporal thinking} within a
wide-range of problem-solving tasks and application areas where collaborative
cognitive systems could serve an assistive and empowering function.Comment: 5 pages, research statement summarising recent publication
State-of-the-art on evolution and reactivity
This report starts by, in Chapter 1, outlining aspects of querying and updating resources on
the Web and on the Semantic Web, including the development of query and update languages
to be carried out within the Rewerse project.
From this outline, it becomes clear that several existing research areas and topics are of
interest for this work in Rewerse. In the remainder of this report we further present state of
the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give
an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs;
in Chapter 4 event-condition-action rules, both in the context of active database systems and
in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks
Temporal Data Modeling and Reasoning for Information Systems
Temporal knowledge representation and reasoning is a major research field in Artificial
Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to
model and process time and calendar data is essential for many applications like appointment
scheduling, planning, Web services, temporal and active database systems, adaptive
Web applications, and mobile computing applications. This article aims at three complementary
goals. First, to provide with a general background in temporal data modeling
and reasoning approaches. Second, to serve as an orientation guide for further specific
reading. Third, to point to new application fields and research perspectives on temporal
knowledge representation and reasoning in the Web and Semantic Web
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