Related papers: AI-Augmented Business Process Management Systems: …
Machine-learning based generation of process models from natural language text process descriptions provides a solution for the time-intensive and expensive process discovery phase. Many organizations have to carry out this phase, before…
BPMN is a specification language widely used by industry and researchers for business process modeling and execution. It defines clearly how to articulate its concepts, but do not provide mechanism to represent the semantics of the produced…
Robotic Process Automation (RPA) is a fast-emerging automation technology that sits between the fields of Business Process Management (BPM) and Artificial Intelligence (AI), and allows organizations to automate high volume routines. RPA…
Data-driven approaches are becoming more common as problem-solving techniques in many areas of research and industry. In most cases, machine learning models are the key component of these solutions, but a solution involves multiple such…
Algorithmic decision support (ADS), using Machine-Learning-based AI, is becoming a major part of many processes. Organizations introduce ADS to improve decision-making and use available data, thereby possibly limiting deviations from the…
The Bayes-Adaptive Markov Decision Process (BAMDP) formalism pursues the Bayes-optimal solution to the exploration-exploitation trade-off in reinforcement learning. As the computation of exact solutions to Bayesian reinforcement-learning…
It has been 100 years since statistical process control (SPC) or statistical process monitoring (SPM) was first introduced for production processes and later applied to service, healthcare, and other industries. The techniques applied to…
Process mining is a new emerging research trend over the last decade which focuses on analyzing the processes using event log and data. The raising integration of information systems for the operation of business processes provides the…
The widespread adoption of complex machine learning models in high-stakes domains has brought the "black-box" problem to the forefront of responsible AI research. This paper aims at addressing this issue by improving the Explainable…
In the era of (multi-modal) large language models, most operational processes can be reformulated and reproduced using LLM agents. The LLM agents can perceive, control, and get feedback from the environment so as to accomplish the given…
Artificial Intelligence (AI) / Machine Learning (ML)-based systems are widely sought-after commercial solutions that can automate and augment core business services. Intelligent systems can improve the quality of services offered and…
In today world, organizations like Google, Yahoo, Amazon, Facebook etc. are facing drastic increase in data. This leads to the problem of capturing, storing, managing and analyzing terabytes or petabytes of data, stored in multiple formats,…
Trust in AI agents has been extensively studied in the literature, resulting in significant advancements in our understanding of this field. However, the rapid advancements in Large Language Models (LLMs) and the emergence of LLM-based AI…
We describe an augmented intelligence system for simplifying and enhancing the modeling experience for operations research. Using this system, the user receives a suggested formulation of an optimization problem based on its description. To…
The implementation of artificial intelligence (AI) in business applications holds considerable promise for significant improvements. The development of AI systems is becoming increasingly complex, thereby underscoring the growing importance…
Embodied systems, where generative autonomous agents engage with the physical world through integrated perception, cognition, action, and advanced reasoning powered by large language models (LLMs), hold immense potential for addressing…
Enterprise content management is an urgent issue of current scientific and practical activities in software design and implementation. However, papers known as yet give insufficient coverage of theoretical background of the software in…
Interprofessional education has long relied on case studies and the use of standardized patients to support teamwork, communication, and related collaborative competencies among healthcare professionals. However, traditional approaches are…
Business Process Simulation (BPS) refers to techniques designed to replicate the dynamic behavior of a business process. Many approaches have been proposed to automatically discover simulation models from historical event logs, reducing the…
As artificial intelligence (AI) systems become increasingly integrated into various domains, ensuring that they align with human values becomes critical. This paper introduces a novel formalism to quantify the alignment between AI systems…