FUN-Agent: A 2020 HUMAINE Competition Entrant

Abstract

Of late, there has been a significant surge of interest in industry and the general populace about future potential of human-AI collaboration [20]. Academic researchers have been pushing the frontier of new modalities of peer-level and ad-hoc human agent collaboration [10;22] for a longer period. We have been particularly interested in research on agents representing human users in negotiating deals with other human and autonomous agents [12;16;18]. Here we present the design for the conversational aspect of our agent entry into the HUMAINE League of the 2020 Automated Negotiation Agent Competition (ANAC). We discuss how our agent utilizes conversational and negotiation strategies, that mimic those used in human negotiations, to maximize its utility as a simulated street vendor. We leverage verbal influence tactics, offer pricing, and increasing human convenience to entice the buyer, build trust and discourage exploitation. Additionally, we discuss the results of some in-house testing we conducted.