Resolving crises through automated bilateral negotiations

Kraus, Sarit; Hoz-Weiss, Penina; Wilkenfeld, Jonathan; Andersen, David R.; Pate, Amy

doi:10.1016/j.artint.2007.05.007

Cited by 58 publications

(22 citation statements)

References 21 publications

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“…There has been a fair amount of previous work in understanding negotiation dialogs, e.g., (Walton and McKersie, 1991;Baker, 1994); as well as agents who can engage in negotiation, e.g. (Jameson et al, 1994;Sidner, 1994;Kraus et al, 2008;Traum et al, 2008). In this paper we investigate the role that dialogue initiative plays in negotiation.…”

Section: Introductionmentioning

confidence: 99%

Initiative Taking in Negotiation

Nouri

Traum

2014

Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

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We examine the relationship between initiative behavior in negotiation dialogues and the goals and outcomes of the negotiation. We propose a novel annotation scheme for dialogue initiative, including four labels for initiative and response behavior in a dialogue turn. We annotate an existing human-human negotiation dataset, and use initiative-based features to try to predict both negotiation goal and outcome, comparing our results to prior work using other (non-initiative) features sets. Results show that combining initiative features with other features leads to improvements over either set and a majority class baseline.

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Section: Introductionmentioning

confidence: 99%

Initiative Taking in Negotiation

Nouri

Traum

2014

Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

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“…The game is then analyzed to find the optimal negotiation strategies for the agent, assuming that people are also optimal with respect to their own utility function. Examples of this approach include Kraus et al [2008] who modeled human bilateral negotiations in a simulated diplomatic crisis characterized by time constraints and deadlines in settings of complete information. They adapted equilibrium strategies to people's behavior using simple heuristics, such as considering certain non-optimal actions.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Agent for Negotiating with People in Different Cultures

Gal

Kraus

Gelfand

et al. 2011

ACM Trans. Intell. Syst. Technol.

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The rapid dissemination of technology such as the Internet across geographical and ethnic lines is opening up opportunities for computer agents to negotiate with people of diverse cultural and organizational affiliations. To negotiate proficiently with people in different cultures, agents need to be able to adapt to the way behavioral traits of other participants change over time. This paper describes a new agent for repeated bilateral negotiation that was designed to model and adapt its behavior to the individual traits exhibited by its negotiation partner. The agent's decisionmaking model combined a social utility function that represented the behavioral traits of the other participant, as well as a rule-based mechanism that used the utility function to make decisions in the negotiation process. The agent was deployed in a strategic setting in which both participants needed to complete their individual tasks by reaching agreements and exchanging resources, the number of negotiation rounds were not fixed in advance and agreements were not binding. The agent negotiated with human subjects in the U.S. and Lebanon in situations that varied the dependency relationships between participants at the onset of negotiation. There was no prior data available about the way people would respond to different negotiation strategies in these two countries. Results showed that the agent was able to adopt a different negotiation strategy to each country. Its average performance across both countries was equal to that of people. However, the agent outperformed people in the United States, because it learned to make offers that were likely to be accepted by people, while being more beneficial to the agent than to people. In contrast, the agent was outperformed by people in Lebanon, because it adopted a high reliability measure which allowed people to take advantage of it. These results provide insight for human-computer agent designers in the types of multi-cultural settings which we considered, showing that adaptation is a viable approach towards the design of computer agents to negotiate with people when there is no prior data of their behavior.

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“…Research in artificial intelligence has proposed a variety of approaches such as "persuasion" [31,60,39,27,48] and negotiation [29,47,77], techniques that aim to convince people through argument or iterative discussion, respectively, to adopt different strategies or choices. The techniques for persuasion require models of the potential for different types of arguments to influence a person to change strategy.…”

Section: Related Workmentioning

confidence: 99%

Problem restructuring for better decision making in recurring decision situations

Elmalech

Sarne

Grosz

2014

Auton Agent Multi-Agent Syst

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This paper proposes the use of restructuring information about choices to improve the performance of computer agents on recurring sequentially dependent decisions. The intended situations of use for the restructuring methods it defines are website platforms such as electronic marketplaces in which agents typically engage in sequentially dependent decisions. With the proposed methods, such platforms can improve agents' experience, thus attracting more customers to their sites. In sequentially-dependent-decisions settings, decisions made at one time may affect decisions made later; hence, the best choice at any point depends not only on the options at that point, but also on future conditions and the decisions made in them. This "problem restructuring" approach was tested on sequential economic search, which is a common type of recurring sequentially dependent decision-making problem that arises in a broad range of areas. The paper introduces four heuristics for restructuring the choices that are available to decision makers in economic search applications. Three of these heuristics are based on characteristics of the choices, not of the decision maker. The fourth heuristic requires information about a decision-makers prior decision-making, which it uses to classify the decision-maker. The classification type is used to choose the best of the three other heuristics. The heuristics were extensively tested on a large number of agents designed by different people with skills similar to those of a typical agent developer. The results demonstrate that the problem-restructuring approach is a promising one for improving the performance of agents on sequentially dependent decisions. Although there was a minor degradation in performance for a small portion of the agents, the overall and average individual performance improved substantially. Complementary experimentation with people demonstrated that the methods carry over, to some extent, also to human decision makers. Interestingly, the heuristic that adapts based on a decision-maker's history achieved the best results for computer agents, but not for people.

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Resolving crises through automated bilateral negotiations

Cited by 58 publications

References 21 publications

Initiative Taking in Negotiation

Initiative Taking in Negotiation

An Adaptive Agent for Negotiating with People in Different Cultures

Problem restructuring for better decision making in recurring decision situations

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