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Process mining represents a methodological approach that facilitates the in-depth analysis of business operations with the aim of revealing significant insights pertaining to their efficacy, efficiency, and regulatory compliance. In a seamless business setting, it's essential to evaluate, refine, and confirm these process models. Traditional methods for checking these models excel in validating their accuracy but cannot handle the inherent probabilistic and real-time behavior of these models. To address this, our research paper presents a new methodology that enhances probabilistic model ...

The field of process mining is experiencing rapid growth, utilizing data science techniques to analyze business processes and uncover insights about their performance, efficiency, and compliance. The process mining approach begins with process discovery, which involves creating process models based on event logs; and depending on the type of models discovered, the correctness of models needs to be guaranteed. Traditional model checking methods are good approaches to verify the correctness of process models, but those methods cannot model the probabilistic nature of the discovered process model...

Allocation and planning with a collection of tasks and a group of agents is an important problem in multiagent systems. One commonly faced bottleneck is scalability, as in general the multiagent model increases exponentially in size with the number of agents. We consider the combination of random task assignment and multiagent planning under multiple-objective constraints, and show that this problem can be decentralised to individual agent-task models. We present an algorithm of point-oriented Pareto computation, which checks whether a point corresponding to given cost and probability threshol...

High-performance data streaming technologies are increasingly adopted in IT companies to support the integration of heterogeneous and possibly distributed applications. Compared with the traditional message queuing middleware, a streaming platform enables the implementation of event-streaming systems (ESS) which include not only complex queues but also pipelines that transform and react to the streams of data. By analysing the centralised data streams, one can evaluate the Quality-of-Service for other systems and components that produce or consume those streams. We consider the exploitation of...