An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour in consensus reaching process under social network group decision making is proposed, which is based on a theoretically sound optimal feedback model. The manipulation behaviour classification is twofold: (1) ‘individual manipulation’ where each expert manipulates his/her own behaviour to achieve higher importance degree (weight); and (2) ‘group manipulation’ where a group of experts force inconsistent experts to adopt specific recommendation advices obtained via the use of fixed feedback parameter. To counteract ‘individual manipulation’, a behavioural weights assignment method modelling sequential attitude ranging from ‘dictatorship’ to ‘democracy’ is developed, and then a reasonable policy for group minimum adjustment cost is established to assign appropriate weights to experts. To prevent ‘group manipulation’, an optimal feedback model with objective function the individual adjustments cost and constraints related to the threshold of group consensus is investigated. This approach allows the inconsistent experts to balance group consensus and adjustment cost, which enhances their willingness to adopt the recommendation advices and consequently the group reaching consensus on the decision making problem at hand. A numerical example is presented to illustrate and verify the proposed optimal feedback model

The induced 2-tuple linguistic generalized OWA operator and its application in linguistic decision making

We present the induced 2-tuple linguistic generalized ordered weighted averaging (2-TILGOWA) operator. This new aggregation operator extends previous approaches by using generalized means, order-inducing variables in the reordering of the arguments and linguistic information represented with the 2-tuple linguistic approach. Its main advantage is that it includes a wide range of linguistic aggregation operators. Thus, its analyses can be seen from different perspectives and we obtain a much more complete picture of the situation considered and are able to select the alternative that best fits with with our interests or beliefs. We further generalize the operator by using quasi-arithmetic means, and obtain the Quasi-2-TILOWA operator. We conclude this paper by analysing the applicability of this new approach in a decision-making problem concerning product management.linguistic decision making, linguistic generalized mean, 2-tuple linguistic owa operator, 2-tuple linguistic aggregation operator

Automated Negotiation for Provisioning Virtual Private Networks Using FIPA-Compliant Agents

This paper describes the design and implementation of negotiating agents for the task of provisioning virtual private networks. The agents and their interactions comply with the FIPA specification and they are implemented using the FIPA-OS agent framework. Particular attention is focused on the design and implementation of the negotiation algorithms

Architecture value mapping: using fuzzy cognitive maps as a reasoning mechanism for multi-criteria conceptual design evaluation

The conceptual design phase is the most critical phase in the systems engineering life cycle. The design concept chosen during this phase determines the structure and behavior of the system, and consequently, its ability to fulfill its intended function. A good conceptual design is the first step in the development of a successful artifact. However, decision-making during conceptual design is inherently challenging and often unreliable. The conceptual design phase is marked by an ambiguous and imprecise set of requirements, and ill-defined system boundaries. A lack of usable data for design evaluation makes the problem worse. In order to assess a system accurately, it is necessary to capture the relationships between its physical attributes and the stakeholders\u27 value objectives. This research presents a novel conceptual architecture evaluation approach that utilizes attribute-value networks, designated as \u27Architecture Value Maps\u27, to replicate the decision makers\u27 cogitative processes. Ambiguity in the system\u27s overall objectives is reduced hierarchically to reveal a network of criteria that range from the abstract value measures to the design-specific performance measures. A symbolic representation scheme, the 2-Tuple Linguistic Representation is used to integrate different types of information into a common computational format, and Fuzzy Cognitive Maps are utilized as the reasoning engine to quantitatively evaluate potential design concepts. A Linguistic Ordered Weighted Average aggregation operator is used to rank the final alternatives based on the decision makers\u27 risk preferences. The proposed methodology provides systems architects with the capability to exploit the interrelationships between a system\u27s design attributes and the value that stakeholders associate with these attributes, in order to design robust, flexible, and affordable systems --Abstract, page iii

A Multicriteria Approach for the Evaluation of the Sustainability of Re-use of Historic Buildings in Venice

The paper presents a multiple criteria model for the evaluation of the sustainability of projects for the economic re-use of historical buildings in Venice. The model utilises the relevant parameters for the appraisal of sustainability, aggregated into three macro-indicators: intrinsic sustainability, context sustainability and economic-financial feasibility. The model has been calibrated by a panel of experts and tested on two reuse hypotheses of the Old Arsenal in Venice. The tests have proven the model to be a useful support in the early stages of evaluation of re-use projects, where economic improvements are to be combined with conservation, as it supports the identification of critical points and the selection of projects, thus providing not only a check-list of variables to be considered, but an appraisal of trade-offs between economic uses and requirements of conservation.Economic Reuse, Historical Building Conservation

Dynamic adaptation of user profiles in recommender systems

In a period of time in which the content available through the Internet increases exponentially and is more easily accessible every day, techniques for aiding the selection and extraction of important and personalised information are of vital importance. Recommender Systems (RS) appear as a tool to help the user in a decision making process by evaluating a set of objects or alternatives and aiding the user at choosing which one/s of them suits better his/her interests or preferences. Those preferences need to be accurate enough to produce adequate recommendations and should be updated if the user changes his/her likes or if they are incorrect or incomplete. In this work an adequate model for managing user preferences in a multi-attribute (numerical and categorical) environment is presented to aid at providing recommendations in those kinds of contexts. The evaluation process of the recommender system designed is supported by a new aggregation operator (Unbalanced LOWA) that enables the combination of the information that defines an alternative into a single value, which then is used to rank the whole set of alternatives. After the recommendation has been made, learning processes have been designed to evaluate the user interaction with the system to find out, in a dynamic and unsupervised way, if the user profile in which the recommendation process relies on needs to be updated with new preferences. The work detailed in this document also includes extensive evaluation and testing of all the elements that take part in the recommendation and learning processes

A dynamic feedback mechanism with attitudinal consensus threshold for minimum adjustment cost in group decision making

This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 71971135, Grant 71571166, Grant 72071056, and Grant 71910107002, in part by the Innovative Talent Training Project of Graduate Students in Shanghai Maritime University of China under Grant 2019YBR017, and in part by the Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/10.13039/501100011033.This article presents a theoretical framework for a dynamic feedback mechanism in group decision making (GDM) by the implementation of an attitudinal consensus threshold (ACT) to generate recommendation advice for the identified inconsistent experts with the aim to increase consensus. The novelty of the approach resides in its ability to implement the ACT continuously, which allows the covering of all possible consensus states of the group from its minimum to maximum consensus degrees. Therefore, it can be flexibly applied to GDM problems with different consistency requirements. A sensitivity analysis method with visual simulation is proposed to support the checking of the numbers of experts involved in the feedback process and the minimum adjustment cost associated with the different ACT intervals. Experimental results show that an increase in the ACT value will lead to an increase in the number of experts and adjustment cost involved in the feedback process. Eventually, a numerical example is included to simulate the feedback process under various decision making scenarios with different ACT intervals.National Natural Science Foundation of China (NSFC) 71971135 71571166 72071056 71910107002Innovative Talent Training Project of Graduate Students in Shanghai Maritime University of China 2019YBR017Spanish Government PID2019-103880RB-I00/AEI/10.13039/50110001103