Johnathan Mell

AAMAS Conference 2025 Conference Paper

Decoding Negotiation Dynamics: The Impact of Opponent Identity and Privacy on Strategy, Deception, and Emotional Transparency in Human-Agent Interaction

• Nusrath Jahan
• Johnathan Mell

Negotiation is a fundamental aspect of human-human and humanagent interactions, shaping decision-making and conflict resolution. As AI systems become increasingly embedded in these contexts, understanding how opponent framing (human vs. AI) and privacy decisions (webcam sharing) influence negotiation strategies merits investigation. This study examines their effects on deception and emotional engagement using the IAGO platform [8], where participants negotiate with an opponent framed as either human or AI while deciding whether to share their webcam. Results demonstrate that participants who withheld webcam data exhibited increased deceptive behavior, which positively influenced negotiation performance, though deception only partially mediated this effect. Although opponent identity did not significantly affect deception or success, participants exhibited higher emotional engagement when negotiating with a human opponent. These results underscore the necessity for privacy-aware, adaptive AI agents that foster engagement and ethical decision-making while aligning with human negotiation strategies.

AAMAS Conference 2024 Conference Paper

Unraveling the Tapestry of Deception and Personality: A Deep Dive into Multi-Issue Human-Agent Negotiation Dynamics

• Nusrath Jahan
• Johnathan Mell

Exploring the intricacies of human behavior in negotiations is pivotal in developing advanced human-agent interaction systems. This study delves into the complex interplay between deception, personality traits, and self-reported truthfulness in the context of humanagent negotiations, leveraging the IAGO platform [34] to facilitate multi-issue bargaining tasks. Our exploration, which also ventures into the realm of agent avatar gender and personality trait display, is centered around understanding how individual personality traits influence deceptive behaviors and perceptions in negotiations. Our findings establish a significant alignment between participants’ selfreported truthfulness and their actual behaviors, underscoring the reliability of self-reports. Moreover, intricate relationships were uncovered between the Big Five personality dimensions—Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism [3, 9]—and human user’s self-reported truthfulness, as well as beliefs about the necessity of deception in negotiations. To illustrate, individuals with higher levels of Openness were more likely to report being truthful but also believed more strongly in the necessity of deception for successful negotiations. These nuanced insights into personality-driven behaviors and perceptions are instrumental in fostering the development of adaptive and sophisticated negotiation agents, enhancing the comprehension of dynamics in humanagent interactions. Our findings present refined perspectives on the congruence and potential divergences between perceived necessity and the actual enactment of deceptive behaviors, laying a robust foundation for future investigations in agent personalization and human-agent interactions within negotiation contexts.

EUMAS Conference 2020 Conference Paper

Challenges and Main Results of the Automated Negotiating Agents Competition (ANAC) 2019

• Reyhan Aydogan
• Tim Baarslag
• Katsuhide Fujita
• Johnathan Mell
• Jonathan Gratch
• Dave de Jonge
• Yasser Mohammad
• Shinji Nakadai

Abstract The Automated Negotiating Agents Competition (ANAC) is a yearly-organized international contest in which participants from all over the world develop intelligent negotiating agents for a variety of negotiation problems. To facilitate the research on agent-based negotiation, the organizers introduce new research challenges every year. ANAC 2019 posed five negotiation challenges: automated negotiation with partial preferences, repeated human-agent negotiation, negotiation in supply-chain management, negotiating in the strategic game of Diplomacy, and in the Werewolf game. This paper introduces the challenges and discusses the main findings and lessons learnt per league.

JAIR Journal 2020 Journal Article

The Effects of Experience on Deception in Human-Agent Negotiation

• Johnathan Mell
• Gale Lucas
• Sharon Mozgai
• Jonathan Gratch

Negotiation is the complex social process by which multiple parties come to mutual agreement over a series of issues. As such, it has proven to be a key challenge problem for designing adequately social AIs that can effectively navigate this space. Artificial AI agents that are capable of negotiating must be capable of realizing policies and strategies that govern offer acceptances, offer generation, preference elicitation, and more. But the next generation of agents must also adapt to reflect their users’ experiences. The best human negotiators tend to have honed their craft through hours of practice and experience. But, not all negotiators agree on which strategic tactics to use, and endorsement of deceptive tactics in particular is a controversial topic for many negotiators. We examine the ways in which deceptive tactics are used and endorsed in non-repeated human negotiation and show that prior experience plays a key role in governing what tactics are seen as acceptable or useful in negotiation. Previous work has indicated that people that negotiate through artificial agent representatives may be more inclined to fairness than those people that negotiate directly. We present a series of three user studies that challenge this initial assumption and expand on this picture by examining the role of past experience. This work constructs a new scale for measuring endorsement of manipulative negotiation tactics and introduces its use to artificial intelligence research. It continues by presenting the results of a series of three studies that examine how negotiating experience can change what negotiation tactics and strategies human endorse. Study #1 looks at human endorsement of deceptive techniques based on prior negotiating experience as well as representative effects. Study #2 further characterizes the negativity of prior experience in relation to endorsement of deceptive techniques. Finally, in Study #3, we show that the lessons learned from the empirical observations in Study #1 and #2 can in fact be induced—by designing agents that provide a specific type of negative experience, human endorsement of deception can be predictably manipulated.

AAMAS Conference 2017 Conference Paper

Grumpy & Pinocchio: Answering Human-Agent Negotiation Questions through Realistic Agent Design

• Johnathan Mell
• Jonathan Gratch

We present the Interactive Arbitration Guide Online (IAGO) platform, a tool for designing human-aware agents for use in negotiation. Current state-of-the-art research platforms are ideally suited for agent-agent interaction. While helpful, these often fail to address the reality of human negotiation, which involves irrational actors, natural language, and deception. To illustrate the strengths of the IAGO platform, the authors describe four agents which are designed to showcase the key design features of the system. We go on to show how these agents might be used to answer core questions in human-centered computing, by reproducing classical human-human negotiation results in a 2x2 human-agent study. The study presents results largely in line with expectations of human-human negotiation outcomes, and helps to demonstrate the validity and usefulness of the IAGO platform. General Terms Experimentation; Human Factors.

IJCAI Conference 2017 Conference Paper

Human-Like Agents for Repeated Negotiation

• Johnathan Mell

Virtual agents have been used as tools in negotiation—from acting as mediators to manifesting as full-fledged conversational partners. Virtual agents are a powerful tool for teaching negotiation skills, but require an accurate model of human behavior to perform well both as partners and teachers. The work proposed here aims to expand the current horizon of virtual negotiating agents to utilize human-like strategies. Further agents developed using this framework should be cognizant of the social factors influencing negotiation, including reputation effects and the implications of long-term repeated relationships. A roadmap of current efforts to develop agent platforms and future expansions is discussed.

AAMAS Conference 2016 Conference Paper

IAGO: Interactive Arbitration Guide Online (Demonstration)

• Johnathan Mell
• Jonathan Gratch