Multi-Context Reasoning in Continuous Data-Flow Environments

Stefan Ellmauthaler
2018 Künstliche Intelligenz  
Die Verleihung des akademischen Grades erfolgt mit Bestehen der Verteidigung am 07. Juni 2018 mit dem Gesamtprädikat magna cum laude. Acknowledgements I thank Gerhard Brewka for being a very helpful thesis advisor and that he gave me the opportunity to move from Vienna to Leipzig for doing research within the scope of my thesis and the projects I am employed at. He always encourages the pursuance of own ideas and research directions, which get further improved by his good and constructive
more » ... ck and support. In addition, he was always caring for my well-being and has always been more dedicated than just being a supervisor and chief. Further thanks to Torsten Schaub for reviewing my thesis. I am grateful for my colleagues which assemble a great cooperative community around the Intelligent Systems Group. They provide a good environment to exchange and discuss ideas, do research, and even communicating on a level where we talk about daily life and personal issues and achievements. Another word of thanks shall be going to my co-authors from Vienna, Lisbon, and Leipzig who made incredible discussions and advances in the field of Argumentation and Multi-Context reasoning possible. Many parts of this work and my employment are funded and supported by the German Research Foundation (DFG) under grants BR − 1817/7 − 1/2 and FOR 1513. So thanks to the German Research Foundation, the Research Unit "1513 Hybrid Reasoning for Intelligent Systems", and all the project partners and associates. Additionally, I want to say "thank you" to all my friends who have spent free time together with me and who have given me more than one suggestion for concerns regarding the finishing of the doctoral study. Further thanks to my mother Ilse, who sadly died too early to see my whole development in Germany and the conclusion of my doctoral study, my father Erhard, and his second wife Brigitte for their support, love, caring and help. Last but not least I am very grateful for having my companion Mandy in my life. Her support and love is very important for me and being able to share a great deal of our time together is a priceless addition to my life. Without all of you my road towards this thesis and the finishing of my doctoral studies would have been way rockier than it was. Thank you In the field of artificial intelligence, research on knowledge representation and reasoning has originated a large variety of formats, languages, and formalisms. Over the decades many different tools emerged to use these underlying concepts and ideas. Each one has been designed with some specific application in mind and are even used nowadays, where the internet is seen as a service to be sufficient for the age of Industry 4.0 and the Internet of Things. In that vision of a connected world, with these many different formalisms and systems, it is imperative to have some unified formal way to exchange information, such as knowledge and belief. Alas, that alone is not enough, because even more systems get integrated into the online world and nowadays we are confronted with a huge amount of continuously flowing data. That means a solution is needed to both, allowing the integration of information and dynamic reaction to the data which is provided in such continuous data-flow environments. This work is aiming to present a unique and novel pair of formalisms to tackle these two important needs and propose an abstract and general solution. We will introduce and discuss reactive Multi-Context Systems, which allow one to utilise different knowledge representation formalisms, so-called contexts which are represented as an abstract logic framework, and exchange their beliefs through the means of bridge rules with other contexts. These multiple contexts need to mutually agree on a common set of beliefs, an equilibrium of belief sets. While different Multi-Context Systems already exist, they are only solving this agreement problem once and are neither considering external data streams, nor are they reasoning continuously over time. reactive Multi-Context Systems will do this by adding means of reacting to input streams and allowing the bridge rules to reason with this new information. In addition we propose two different kind of bridge rules, declarative ones which are used to find a mutual agreement and operational ones to adapt the current knowledge for future computations. The second framework is even more abstract and allows computations to happen in an asynchronous way. These asynchronous Multi-Context Systems are aimed at modelling and describing communication between contexts, with different levels of self-management and centralised management of communication and computation. In this thesis, the reactive Multi-Context Systems, will be analysed with respect to usability, consistency management, and computational complexity, while we will show how asynchronous Multi-Context Systems can be used to capture the asynchronous ideas and how to model a reactive Multi-Context System with it. Finally we will show how reactive Multi-Context Systems are positioned in the current world of stream reasoning and that it can capture currently used technologies and therefore allows one to seamlessly connect different systems of these kinds with each other. Further on this also shows that reactive Multi-Context Systems are expressive enough to simulate the mechanics used by these systems to compute the corresponding results on its own as an alternative to the already existing ones. iii For asynchronous Multi-Context Systems, we will discuss how to use them and that they are a very versatile tool to describe communication and asynchronous computation. In addition it will be shown that they can capture the notion of reactive Multi-Context Systems and therefore providing means to only synchronise groups of contexts while allowing the other contexts to operate asynchronously. iv
doi:10.1007/s13218-018-00570-1 fatcat:sx5u3f5t55dwvecab7n72wmusi