Measuring and analyzing agents’ uncertainty in argumentation-based negotiation dialogue games

Marey, Omar; Bentahar, Jamal; Dssouli, Rachida; Mbarki, Mohamed

doi:10.1016/j.eswa.2013.07.005

Cited by 19 publications

(3 citation statements)

References 28 publications

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“…Marey et al (2014a) published a paper where they included uncertainty in argumentation-based negotiation. This work came in the sequence of the one presented in Marey et al (2014b). They conducted a case study (buyer/seller scenario) based on their proposed approach and concluded that with their techniques negotiating agents achieve better results than non-negotiating agents.…”

Section: Related Workmentioning

confidence: 99%

Dynamic argumentation in UbiGDSS

et al. 2017

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Supporting and representing the group decision-making process is a complex task that requires very specific aspects. The current existing argumentation models cannot make good use of all the advantages inherent to group decision-making. There is no monitoring of the process or the possibility to provide dynamism to it. These issues can compromise the success of Group Decision Support Systems if those systems are not able to provide freedom and all necessary mechanisms to the decision-maker. We investigate the use of argumentation in a completely new perspective that will allow for a mutual understanding between agents and decision-makers. Besides this, our proposal allows to define an agent not only according to the preferences of the decisionmaker but also according to his interests towards the decision-making process. We show that our definition respects the requirements that are essential for groups to interact without limitations and that can take advantage of those interactions to create valuable knowledge to support more and better.

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Section: Related Workmentioning

confidence: 99%

Dynamic argumentation in UbiGDSS

et al. 2017

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“…Hence, the proposed model could be extended to deal with this kind of preference relations. Third, to facilitate the achievement of agreements and negotiate them, automatic argumentation methods could be incorporated into the proposed model [43][44][45] . And, fourth, it could be applied to other areas related to green manufacturing [46] .…”

Section: Discussionmentioning

confidence: 99%

Adaptive multi-criteria group decision-making model based on consistency and consensus with intuitionistic reciprocal preference relations: a case study in energy storage technology selection

Cabrerizo¹,

Trillo²,

Alonso³

et al. 2022

J Smart Environ Green Comput

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Aim: This study aims to present a multi-criteria group decision-making model with intuitionistic reciprocal preference relations that incorporates a new feedback mechanims adapting its operation to the decision-makers' consistency. Methods: A new adaptive feedback mechanism is developed within a multi-criteria group decision-making model. Assuming different kinds of decision-makers classified according to their consistency, this feedback mechanism customizes the recommendations given by adopting three strategies to identify the problematic assessments that the decision-makers should change if they want to collaborate to increase the consensus. Results: The performance of the proposed model is shown in a case study for the selection of an energy storage technology. It shows that the decision-makers providing assessments with low consistency must modify more assessments, allowing the most consistent decision-makers to be the leaders of the negotiation and persuade the others to adjust their assessments to improve the agreement achieved. Conclusion: In this study, a novel multi-criteria group decision-making model is developed. It includes an adaptive feedback mechanism adjusting the advice provided by considering the decision-makers' consistency. It allows that the assessments of the most consistent decision-makers never be strongly modified during the decision process.

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“…Computing the uncertainty can help to reduce the effect of ignorance existing in the calculation of trustworthiness. The probability certainty distribution model (PCDM) that was presented by Hang et al (2008) calculates the trustworthiness of each agent according to the posterior probability of satisfying and dissatisfying interactions and the uncertainty placed in the probability (Marey et al, 2014;Wang and Singh, 2010). This model is based on the probability theory that divides the outcomes of past interactions into positive (satisfying) and negative (dissatisfying) outcomes.…”

Section: Uncertaintymentioning

confidence: 99%

An incorporated RUU model for multi-agent systems in e-commerce

Majd

Hobson

2020

JEIM

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PurposeThe purpose of this paper is to enhance trust in e-commerce multi-agent systems by presenting a model, called RUU, to select the most trustworthy provider agent based on learning from previous interactions and computing reliability, unreliability and uncertainty.Design/methodology/approachThe methodology comprises analyzing the most representative existing trust models, while a new concept was proposed and measured as unreliability. To make decision about the agents, RUU integrated reliability, unreliability and uncertainty components and used the TOPSIS multi-criteria decision method to select the most trustworthy provider agent. To evaluate the RUU model, the experimentation was carried out in two stages. First, the average accuracy of the model was investigated by simulating RUU in a multi-agent environment. Second, the performance of the model was compared with other related trust models.FindingsThe experimental results revealed that RUU model outperforms current models in providing accurate credibility measurements and computing an accurate trust mechanism for agents, also presenting a decision-making process to choose the most trustworthy provider agent.Research limitations/implicationsThe model presented based on different mathematical computations that take time to be calculated, which is a big limitation of computational models.Practical implicationsRUU enables an agent to make effective and sound decisions in light of the uncertainty that exists in e-commerce multi-agent environments.Originality/valueThis paper is beneficial to enhance the fulfilment of purchasing between provider and requester agents. In fact, the proposed model can ensure critical transactions performed securely in e-commerce multi-agent environments.

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Measuring and analyzing agents’ uncertainty in argumentation-based negotiation dialogue games

Cited by 19 publications

References 28 publications

Dynamic argumentation in UbiGDSS

Dynamic argumentation in UbiGDSS

Adaptive multi-criteria group decision-making model based on consistency and consensus with intuitionistic reciprocal preference relations: a case study in energy storage technology selection

An incorporated RUU model for multi-agent systems in e-commerce

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