2019/09/09 by Ryuta Arisaka, Arisaka, Ryuta, Makoto Hagiwara +3
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Auction Theory and Applications #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Multi-Agent Systems and Negotiation
paper · pdf · doi:10.48550/arxiv.1909.03616
openalex publication_date 2019/09/09 · openalex created_date 2019/09/12 · openalex updated_date 2026/07/28
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.