Formulating Manipulable Argumentation with Intra-/Inter-Agent Preferences

TL;DR

This paper develops an argumentation-theoretic model for multi-agent systems that can manipulate information through deception, using intra- and inter-agent preferences to detect deception and influence trust and argument acceptance.

Contribution

It introduces a novel framework incorporating intra- and inter-agent preferences to model deception, trust, and argument acceptability in manipulable multi-agent argumentation.

Findings

Intra-agent preferences help detect deception and honesty.

Inter-agent preferences influence trustworthiness assessments.

Deception detection impacts argument acceptance and trust judgments.

Abstract

From marketing to politics, exploitation of incomplete information through selective communication of arguments is ubiquitous. In this work, we focus on development of an argumentation-theoretic model for manipulable multi-agent argumentation, where each agent may transmit deceptive information to others for tactical motives. In particular, we study characterisation of epistemic states, and their roles in deception/honesty detection and (mis)trust-building. To this end, we propose the use of intra-agent preferences to handle deception/honesty detection and inter-agent preferences to determine which agent(s) to believe in more. We show how deception/honesty in an argumentation of an agent, if detected, would alter the agent's perceived trustworthiness, and how that may affect their judgement as to which arguments should be acceptable.