When Will Negotiation Agents Be Able to Represent Us? The Challenges and Opportunities for Autonomous Negotiators

Baarslag, Tim; Kaisers, Michael; Gerding, Enrico H.; Jonker, Catholijn M.; Gratch, Jonathan

doi:10.24963/ijcai.2017/653

Cited by 47 publications

(34 citation statements)

References 29 publications

(4 reference statements)

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“…The results presented in this article come from the online version of the Lemon Car Game. In the future we would like to use the computer-mediated game in the person-to-person modality-i.e., have two human players play via a screen, rather than face-to-face (e.g., Colored Trails (Ficici et al 2008))-as well as to explore how computer software agents can assist the negotiators (Baarslag et al 2017). The growth in electronic negotiations in international business incentives this research (Melzer and Schoop 2016).…”

Section: Resultsmentioning

confidence: 99%

The Lemon Car Game Across Cultures: Evidence of Relational Rationality

et al. 2019

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In cross-cultural business negotiation, culture is known to influence negotiation processes. As a lens to study this effect we deployed the Lemon Car Game, an online negotiation game developed for this purpose (Hofstede et al. in: Proceedings of 39th international simulation and gaming association conference (ISAGA). Technologia, Kaunas, pp 39-46, 2009a; Hofstede et al. in: David, Sichman (eds) Multi-agentbased simulation IX, international workshop, MABS 2008, revised selectedpapers, LNAI 5269. Springer, Berlin, pp 1-16, 2009b). In this article we report the results from the game, obtained from over 800 players from more than 70 countries. We employ several complementary analyses in a mixed-methods approach. Our findings show that to make sense of the players' actions during negotiation, economic rationality falls short. A pan-cultural individual-level analysis of actions and stated intentions also fails to yield a coherent picture. Within countries, however, actions and intentions do cohere, as shown by an ecological country-level factor analysis, from which three factors emerge for the sellers at country level: trustworthiness, opportunism, and fairness. We conclude from these findings that, in this game, players are driven by what we call relational rationality: they are rational from the perspective of the social world in which they live, with interpersonal relationships weighing heavily. Relational rationality changes players' perspective of economic rationality, and thus their observed behaviour in negotiation. Based on this evidence, we extrapolate that relational rationality significantly influences negotiation processes in all cultures.

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Section: Resultsmentioning

confidence: 99%

The Lemon Car Game Across Cultures: Evidence of Relational Rationality

et al. 2019

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“…Automated negotiation research revealed several benefits that computerized negotiation can offer to e-markets. These benefits include: (1) better deal (win-win settlement); (2) decreased transaction cost and time associated with human operation; (3) increased efficiency of settlements even for semi-structured, multi-issue business bargaining problems; and (4) minimizing of some negative aspects of human negotiation, such as avoiding face-to-face encounters with people who are uncomfortable with "bargaining" [5,16,17]. Unfortunately, a poorly designed automated negotiation agent will not be able to deal effectively with a skillful human counterpart that can adopt flexible strategies [5,17].…”

Section: Study Backgroundmentioning

confidence: 99%

A Study of Integrative Bargaining Model with Argumentation-Based Negotiation

et al. 2019

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E-commerce is increasingly competitive and there is a constant need for new approaches and technology to facilitate exchange. Emerging techniques include the use of artificial intelligence (AI). One AI tool that has sparked interest in e-commerce is the automated negotiation agent (negotiation-agent). This study examines such agents, and proposes an offer strategy model of integrative negotiation for a negotiation-agent with a focus on negotiation agent-to-human interaction. More specifically, a new offer strategy was developed based on the integrative bargaining model, which emphasizes the importance of exchanging information among negotiators and multi-issue negotiation that includes package offers to achieve an integrative (win-win) outcome. This study incorporated an argumentation-based negotiation and the negotiation tactic of multiple equivalent simultaneous offers, which was programmed into the negotiation-agent. An experiment was conducted performing 49 negotiation-agent-to-human negotiations over three issues in online purchase tasks to demonstrate the effectiveness of the proposed strategy. Experimental results indicated that the proposed offer strategy with agent negotiation can enhance the persuasiveness of an offer and the performance of negotiation outcome (human counterpart's perception toward negotiation process, opponent-agent and desire for future negotiation). The findings confirmed the effectiveness of the proposed design and demonstrated an innovative approach to e-commerce transactions.

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“…The topic of automated negotiation has received wide attention in the literature due to its importance as one way of communication between agents and also between agents and humans [3,17,18]. In a general automated negotiation, an agent may need to negotiate with other agents or humans whose (personality) type may not be known [2,24].…”

Section: Introductionmentioning

confidence: 99%

Inferring Personality Types for Better Automated Negotiation

Pucha

Paruchuri

2020

Lecture Notes in Business Information Processing

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Automated negotiation between computational agents or between agents and humans has been a subject of active research with a focus on obtaining better quality solutions within reasonable time frames. The critical issue negotiators face during automated negotiation is that a negotiator may not always know the personality type of the opponent. Studies show that having information about the opponent improves the outcome of negotiation in general. However, unless there is prior knowledge, learning the opponent type in the limited amount of time or number of rounds in a negotiation is a difficult task. In this paper, we use a Partially Observable Markov Decision Process (POMDP) based modeling to perform better modeling of the opponent personality type. In particular, we focus on modeling the opponent into four different types to showcase that a better understanding of personality type can improve the outcome of automated negotiation. Our experiments performed using data sets generated from the IAGO software showcase that we indeed obtain better negotiation outcomes with a higher classification accuracy of the opponent personality type.

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When Will Negotiation Agents Be Able to Represent Us? The Challenges and Opportunities for Autonomous Negotiators

Cited by 47 publications

References 29 publications

The Lemon Car Game Across Cultures: Evidence of Relational Rationality

The Lemon Car Game Across Cultures: Evidence of Relational Rationality

A Study of Integrative Bargaining Model with Argumentation-Based Negotiation

Inferring Personality Types for Better Automated Negotiation

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