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Timotheus Kampik

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12 papers

2 author rows

AAMAS Conference 2026 Conference Paper

Equilibria in Quantitative Bipolar Argumentation Dialogues

Andreas Brännström
Timotheus Kampik

We introduce MQBAFs, multi-agent extensions of quantitative bipolar argumentation frameworks (QBAFs). In MQBAFs, agents have objectives to maximise or minimise the strengths of some arguments, andestablishpreferencesovertheseobjectives. Agentsmake utterances by adding or removing arguments or attacks to/from a QBAF, or by changing arguments’ initial strengths. We then define equilibria for MQBAFs, in which no rational agent would make any additional utterance. The notion of MQBAF opens quantitative bipolar argumentation to principled strategic analysis.

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AAMAS Conference 2026 Conference Paper

Strength Change Explanations in Quantitative Argumentation

Timotheus Kampik
Xiang Yin
Nico Potyka
Francesca Toni

In order to make argumentation-based inference contestable, it is crucial to explain what changes can achieve a desired (instead of the contested) inference result. To this end, we introduce strength change explanations for quantitative (bipolar) argumentation graphs. Strength change explanations describe changes to the initial strengths of a subset of the arguments in a given graph that can achieve a desired ordering based on the final strengths of some (potentially different) subset of arguments. We show that the existing notions of inverse and counterfactual problems can be reduced to strength change explanations. We also prove basic soundness and completeness properties of our strength change explanations, and demonstrate their existence and non-existence in some special cases. By applying a heuristic search, we demonstrate that we can often successfully find strength change explanations for layered graphs that are common in typical application scenarios; still, limitations remain for settings where we do not provide guarantees for the presence (or absence) of explanations.

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FLAP Journal 2025 Journal Article

Cautious Nonmonotonicity

Timotheus Kampik

A key intuition in symbolic artificial intelligence is that an intelligent sys- tem should be non-monotonic, but cautiously so: previous conclusions should only be revised if a compelling reason for doing so exists. In this paper, I trace the evolution of this intuition, which emerged from Dov Gabbay’s seminal 1985 paper and gained additional prominence as cautious monotonicity in the 1990 KLM paper, as well as in an earlier paper by Makinson. I introduce the term cautious nonmonotonicity for the general idea of assuring that monotonicity is satisfied given some condition, thus highlighting that it is the violation, and not the satisfaction, of monotonicity that we need to be careful about. Also, I discuss why cautious nonmonotonicity still is an open problem in theory and practice, and present some results that highlight the intricacy of cautious non- monotonicity in the simple case of abstract argumentation, where inferences are drawn from directed graphs without further structure.

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JAAMAS Journal 2025 Journal Article

Disagree and commit: degrees of argumentation-based agreements

Timotheus Kampik
Juan Carlos Nieves

Abstract In cooperative human decision-making, agreements are often not total; a partial degree of agreement is sufficient to commit to a decision and move on, as long as one is somewhat confident that the involved parties are likely to stand by their commitment in the future, given no drastic unexpected changes. In this paper, we introduce the notion of agreement scenarios that allow artificial autonomous agents to reach such agreements, using formal models of argumentation, in particular abstract argumentation and value-based argumentation. We introduce the notions of degrees of satisfaction and (minimum, mean, and median) agreement, as well as a measure of the impact a value in a value-based argumentation framework has on these notions. We then analyze how degrees of agreement are affected when agreement scenarios are expanded with new information, to shed light on the reliability of partial agreements in dynamic scenarios. An implementation of the introduced concepts is provided as part of an argumentation-based reasoning software library.

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EUMAS Conference 2024 Conference Paper

Can Proof Assistants Verify Multi-agent Systems?

Julian Alfredo Mendez
Timotheus Kampik

Abstract 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 only to Scala, a strongly statically typed high-level programming language, but also to Lean, a proof assistant and programming language. Given these capabilities, Soda can implement multi-agent systems, or parts thereof, that can then be integrated into a mainstream software ecosystem on the one hand and formally verified with state-of-the-art tools on the other hand. We provide a brief and informal introduction to Soda and the aforementioned interoperability capabilities, as well as a simple demonstration of how interaction protocols can be designed and verified with Soda. In the course of the demonstration, we highlight challenges with respect to real-world applicability.

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AAMAS Conference 2023 Conference Paper

TDD for AOP: Test-Driven Development for Agent-Oriented Programming

Cleber Jorge Amaral
Jomi Fred Hübner
Timotheus Kampik

This demonstration paper introduces native test-driven development capabilities that have been implemented in an agent-oriented programming language, in particular as extensions of AgentSpeak. We showcase how these capabilities can facilitate the testing and continuous integration of agents in JaCaMo multi-agent systems.

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AIJ Journal 2022 Journal Article

The quest of parsimonious XAI: A human-agent architecture for explanation formulation

Yazan Mualla
Igor Tchappi
Timotheus Kampik
Amro Najjar
Davide Calvaresi
Abdeljalil Abbas-Turki
Stéphane Galland
Christophe Nicolle

With the widespread use of Artificial Intelligence (AI), understanding the behavior of intelligent agents and robots is crucial to guarantee successful human-agent collaboration since it is not straightforward for humans to understand an agent's state of mind. Recent empirical studies have confirmed that explaining a system's behavior to human users fosters the latter's acceptance of the system. However, providing overwhelming or unnecessary information may also confuse the users and cause failure. For these reasons, parsimony has been outlined as one of the key features allowing successful human-agent interaction with parsimonious explanation defined as the simplest explanation (i. e. least complex) that describes the situation adequately (i. e. descriptive adequacy). While parsimony is receiving growing attention in the literature, most of the works are carried out on the conceptual front. This paper proposes a mechanism for parsimonious eXplainable AI (XAI). In particular, it introduces the process of explanation formulation and proposes HAExA, a human-agent explainability architecture allowing to make it operational for remote robots. To provide parsimonious explanations, HAExA relies on both contrastive explanations and explanation filtering. To evaluate the proposed architecture, several research hypotheses are investigated in an empirical user study that relies on well-established XAI metrics to estimate how trustworthy and satisfactory the explanations provided by HAExA are. The results are analyzed using parametric and non-parametric statistical testing.

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IS Journal 2021 Journal Article

Argumentation-Based Health Information Systems: A Design Methodology

Helena Lindgren
Timotheus Kampik
Esteban Guerrero Rosero
Madeleine Blusi
Juan Carlos Nieves

In this article, we present a design methodology for argumentation-based health information systems. With a focus on the application of formal argumentation, the methodology aims at eliciting requirements in regard to argumentation reasoning behavior, knowledge and user models, and business logic on levels below and above the argumentation layer. We highlight specific considerations that need to be made dependent on the system type, i. e. , for clinical decision-support systems, patient-facing systems, and administration systems. In addition, we outline challenges in regard to the design of argumentation-based intelligent systems for healthcare, considering the state of the art of argumentation research, health information systems, and software design methods. For each challenge, we outline a mitigation strategy.

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AAMAS Conference 2021 Conference Paper

Autonomous Agents on the Edge of Things

Timotheus Kampik
Andres Gomez
Andrei Ciortea
Simon Mayer

This paper describes a demonstration setup that integrates cognitive agents with the latest W3C standardization efforts for the Web of Things (WoT). The conceptual foundations of the implemented system are the integration of cognitive agent abstractions with W3C Web Things, which are generic abstractions of devices and virtual services that provide agents with various interaction affordances (e. g. , actions, events). Together with the W3C WoT Scripting API, which is an ECMAScript-compatible API for W3C WoT environments, these standards allow JavaScript-based agents to be deployed and to operate in heterogeneous WoT environments. The agents can then be effectively distributed across the physical-virtual space in a write once, run anywhere manner: we deploy agents across a heterogeneous information system landscape that includes Web servers, browser-based front-ends, and constrained devices (microcontrollers). The deployment only requires minor platform-specific adjustments to consider resource and performance limitations on constrained devices. As a running example, we demonstrate a semiautonomous assembly scenario with human-in-the-loop support.

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AAMAS Conference 2021 Conference Paper

Toward Consistent Agreement Approximation in Abstract Argumentation and Beyond

Timotheus Kampik
Juan Carlos Nieves

In cooperative human decision-making, agreements are often not total; a partial degree of agreement is sufficient to commit to a decision and move on, as long as one is somewhat confident that the involved parties are likely to stand by their commitment in the future, given no drastic unexpected changes. In this work, we introduce models that allow autonomous agents to reach such agreements, using abstract argumentation as the underlying model.

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AAMAS Conference 2019 Conference Paper

Empathic Agents: A Hybrid Normative/Consequentialistic Approach

Timotheus Kampik

Complex information systems operate with increasing degrees of autonomy. Consequently, such systems should not only optimize for simple metrics (like clicks and views) that reflect the system provider’s preferences but also consider norms or rules, as well as the preferences of other agents that are affected by the systems’ actions. As a means to achieve such behavior, we propose the design and development of empathic agents that use a mixed rule/utilitybased approach when deciding on how to act, considering both their own and others’ utility functions. The agents make use of formal argumentation to reach an agreement on how to act in case of inconsistent beliefs. A promising domain for applying our empathic agents is recommender systems.

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EUMAS Conference 2018 Conference Paper

Implementing Argumentation-Enabled Empathic Agents

Timotheus Kampik
Juan Carlos Nieves
Helena Lindgren

Abstract In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis, we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.

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