3 research outputs found
A Strategy for Implementing description Temporal Dynamic Algorithms in Dynamic Knowledge Graphs by SPIN
Planning and reasoning about actions and processes, in addition to reasoning
about propositions, are important issues in recent logical and computer science
studies. The widespread use of actions in everyday life such as IoT, semantic
web services, etc., and the limitations and issues in the action formalisms are
two factors that lead us to study how actions are represented.
Since 2007, there have been some ideas to integrate Description Logic (DL)
and action formalisms for representing both static and dynamic knowledge.
Meanwhile, time is an important factor in dynamic situations, and actions
change states over time. In this study, on the one hand, we examined related
logical structures such as extensions of description logics (DLs), temporal
formalisms, and action formalisms. On the other hand, we analyzed possible
tools for designing and developing the Knowledge and Action Base (KAB).
For representation and reasoning about actions, we embedded actions into DLs
(such as Dynamic-ALC and its extensions). We propose a terminable algorithm for
action projection, planning, checking the satisfiability, consistency,
realizability, and executability, and also querying from KAB. Actions in this
framework were modeled with SPIN and added to state space. This framework has
also been implemented as a plugin for the Prot\'eg\'e ontology editor.
During the last two decades, various algorithms have been presented, but due
to the high computational complexity, we face many problems in implementing
dynamic ontologies. In addition, an algorithm to detect the inconsistency of
actions' effects was not explicitly stated. In the proposed strategy, the
interactions of actions with other parts of modeled knowledge, and a method to
check consistency between the effects of actions are presented. With this
framework, the ramification problem can be well handled in future works
Temporalised Description Logics for Monitoring Partially Observable Events
Inevitably, it becomes more and more important to verify that the systems surrounding us have certain properties. This is indeed unavoidable for safety-critical systems such as power plants and intensive-care units. We refer to the term system in a broad sense: it may be man-made (e.g. a computer system) or natural (e.g. a patient in an intensive-care unit). Whereas in Model Checking it is assumed that one has complete knowledge about the functioning of the system, we consider an open-world scenario and assume that we can only observe the behaviour of the actual running system by sensors. Such an abstract sensor could sense e.g. the blood pressure of a patient or the air traffic observed by radar.
Then the observed data are preprocessed appropriately and stored in a fact base. Based on the data available in the fact base, situation-awareness tools are supposed to help the user to detect certain situations that require intervention by an expert. Such situations could be that the heart-rate of a patient is rather high while the blood pressure is low, or that a collision of two aeroplanes is about to happen.
Moreover, the information in the fact base can be used by monitors to verify that the system has certain properties. It is not realistic, however, to assume that the sensors always yield a complete description of the current state of the observed system. Thus, it makes sense to assume that information that is not present in the fact base is unknown rather than false. Moreover, very often one has some knowledge about the functioning of the system. This background knowledge can be used to draw conclusions about the possible future behaviour of the system. Employing description logics (DLs) is one way to deal with these requirements. In this thesis, we tackle the sketched problem in three different contexts: (i) runtime verification using a temporalised DL, (ii) temporalised query entailment, and (iii) verification in DL-based action formalisms