49 citations · 80 across the 44 of their papers we have counts for
13 papers · 1 filter
Specification, Application, and Operationalization of a Metamodel of Fairness
Julian Alfredo Mendez, Timotheus Kampik
This paper presents the AR fairness metamodel, aimed at formally representing, analyzing, and comparing fairness scenarios. The metamodel provides an abstract representation of fai…
llmSHAP: A Principled Approach to LLM Explainability
Filip Naudot, Tobias Sundqvist, Timotheus Kampik
Feature attribution methods help make machine learning-based inference explainable by determining how much one or several features have contributed to a model's output. A particula…
Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Abdur Rehman Anwar Qureshi, Adrian Rebmann, Timotheus Kampik +2
Business process management is increasingly practiced using data-driven approaches. Still, classical imperative process models, which are typically formalized using Petri nets, are…
Change in Quantitative Bipolar Argumentation: Sufficient, Necessary, and Counterfactual Explanations
Timotheus Kampik, Kristijonas Čyras, José Ruiz Alarcón
This paper presents a formal approach to explaining change of inference in Quantitative Bipolar Argumentation Frameworks (QBAFs). When drawing conclusions from a QBAF and updating…
Set Contribution Functions for Quantitative Bipolar Argumentation and their Principles
Filip Naudot, Andreas Brännström, Vicenç Torra +1
We present functions that quantify the contribution of a set of arguments in quantitative bipolar argumentation graphs to (the final strength of) an argument of interest, a so-call…
Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Shahrzad Khayatbashi, Majid Rafiei, Jiayuan Chen +3
Object-Centric Process Mining enables the analysis of complex operational behavior by capturing interactions among multiple business objects (e.g., orders, items, deliveries). Thes…
Contestability in Quantitative Argumentation
Xiang Yin, Nico Potyka, Antonio Rago +2
Contestable AI requires that AI-driven decisions align with human preferences. While various forms of argumentation have been shown to support contestability, Edge-Weighted Quantit…
Privacy-Preserving Inconsistency Measurement
Carl Corea, Timotheus Kampik, Nico Potyka
We investigate a new form of (privacy-preserving) inconsistency measurement for multi-party communication. Intuitively, for two knowledge bases K_A, K_B (of two agents A, B), our r…
Implementing Agents in JavaScript
Timotheus Kampik
This chapter gives an introduction to agent-oriented programming in JavaScript. It provides an example-based walk-through of how to implement abstractions for reasoning loop agents…
Conversational Process Model Redesign
Nataliia Klievtsova, Timotheus Kampik, Juergen Mangler +1
With the recent success of large language models (LLMs), the idea of AI-augmented Business Process Management systems is becoming more feasible. One of their essential characterist…
Identifying Process Improvement Opportunities through Process Execution Benchmarking
Luka Abb, Majid Rafiei, Timotheus Kampik +1
Benchmarking functionalities in current commercial process mining tools allow organizations to contextualize their process performance through high-level performance indicators, su…
Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processes
Hoang Vu, Nataliia Klievtsova, Henrik Leopold +2
With the rise of generative AI, industry interest in software agents is growing. Given the stochastic nature of generative AI-based agents, their effective and safe deployment in o…
Can Proof Assistants Verify Multi-Agent Systems?
Julian Alfredo Mendez, Timotheus Kampik
This paper presents the Soda language for verifying multi-agent systems. Soda is a high-level functional and object-oriented language that supports the compilation of its code not…