Author name cluster

Andreas Brännström

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4 papers

1 author row

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

No Future for LLM-based Agents without Formal Dialogue Verification

Juan Carlos Nieves
Andreas Brännström
Esteban Guerrero

With the arrival of Large Language Models (LLMs), there is an explosion of agents characterised in terms of LLM-prompts. But LLMs lack consistency with their answers, and they are prone to hallucinations. ThismeansthatLLM-basedagentsareerraticagents. Hence, there are no guarantees that LLM-based agents will be aligned with an expected behaviour. We argue that formal dialogue verification is the way to go for minimising the potential negative side effects of erratic LLM-based agents. Erratic LLM-based agents are far from complying with basic Trustworthy AI principles such as technical robustness and safety. Formal Dialogue Verification methods provide rigorous mathematical frameworks for verifying fundamental behavioral properties of LLM-based agents.

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AAMAS Conference 2025 Conference Paper

Formal Verification of Manipulation Dialogues

Andreas Brännström
Chiaki Sakama
Juan Carlos Nieves

We introduce a formal framework for recognizing manipulation in human-agent interactions, where one agent gradually influences another’s beliefs. To this end, we extend Quantitative Bipolar Argumentation Frameworks (QBAFs) by incorporating agents’ beliefs about arguments, attacks, and supports, forming QBAF with Belief (QBAFB). By defining axioms of belief change and integrating QBAFB into dialogue games, we establish conditions for manipulation—belief change, concealment, and intent—where strategies are shaped by (dis)honesty. The framework generates belief state trajectories, serving as explanations for manipulation.

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AAMAS Conference 2023 Conference Paper

A Formal Framework for Deceptive Topic Planning in Information-Seeking Dialogues

Andreas Brännström
Virginia Dignum
Juan Carlos Nieves

This paper introduces a formal framework for goal-hiding informationseeking dialogues to deal with interactions where a seeker agent estimates a human respondent to not be willing to share the soughtfor information. Hence, the seeker postpones (hides) a sensitive goal topic until the respondent is perceived willing to talk about it. This regards a type of deceptive strategy to withhold information, e. g. , a sensitive question, that, in a given dialogue state, may be harmful to a respondent, e. g. , by violating privacy. The framework uses Quantitative Bipolar Argumentation Frameworks to assign willingness scores to topics, inferred from a respondent’s asserted beliefs. A gradual semantics is introduced to handle changes in willingness scores based on relations among topics. The goal-hiding dialogue process is illustrated using an example inspired by primary healthcare nurses’ strategies for collecting sensitive health information from patients.

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