Formulating Manipulable Argumentation with Intra-/Inter-Agent Preferences
This work addresses the challenge of manipulation in argumentation systems for applications like marketing and politics, but it is incremental as it builds on existing argumentation-theoretic models.
The paper tackles the problem of modeling deceptive communication in multi-agent argumentation by introducing intra-agent preferences for deception detection and inter-agent preferences for trust assessment, showing how detected deception alters perceived trustworthiness and influences argument acceptability.
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.