Academic literature on the topic 'Fairness modeling'

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Journal articles on the topic "Fairness modeling"

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Liu, Guangdong, Jingxiu Song, Jinggui Chen, Ziyang Li, and Huagui Zhu. "Ordering Decisions of Supply Chain with Competition and Dual-Fairness Concern." Discrete Dynamics in Nature and Society 2022 (August 19, 2022): 1–14. http://dx.doi.org/10.1155/2022/9811993.

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This study studies a supply chain consisting of one supplier and two retailers and analyzes the optimal decisions of ordering quantity in four types of no fairness concern, horizontal fairness concern, vertical fairness concern, and dual-fairness concern and the impacts of fairness concern on supply chain. The results show that (1) vertical fairness concern can decrease the ordering quantity of the retailer with vertical fairness concern and the wholesale price and improve the ordering quantity of the retailer without fairness concern; (2) horizontal fairness concern can increase the ordering quantity of the retailer with horizontal fairness concern and improve the ordering quantity of the retailer without fairness concern, but does not influence the wholesale price; and (3) dual-fairness concern can decrease the ordering quantity of the retailer with dual-fairness concern and the wholesale price and improve the ordering quantity of the retailer without fairness concern as a whole. The numerical analysis also proves the findings.
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Diekmann, Sven, and Sjoerd D. Zwart. "Modeling for fairness: A Rawlsian approach." Studies in History and Philosophy of Science Part A 46 (June 2014): 46–53. http://dx.doi.org/10.1016/j.shpsa.2013.11.001.

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Bandyopadhyay, Anup Kumar. "Modeling fairness and starvation in concurrent systems." ACM SIGSOFT Software Engineering Notes 32, no. 6 (November 2007): 2. http://dx.doi.org/10.1145/1317471.1317474.

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Wei, Guangxing, Xu Zhang, Xinghong Qin, and Binta Bary. "Operational Strategy for Low-Carbon Supply Chain under Asymmetric Information of Fairness Concerns." Discrete Dynamics in Nature and Society 2022 (February 10, 2022): 1–22. http://dx.doi.org/10.1155/2022/7655745.

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Carbon emission reduction has become a common hot topic around the world. Although the previous literature has proven that the asymmetric information and fairness concerns would influence the operational strategy for low-carbon supply chain, it hardly touched the asymmetric information of fairness concerns, which contradicted practical observations and experimental evidence. Incorporating the asymmetric information of fairness concerns, this paper investigates a low-carbon supply chain consisting of a manufacturer and a retailer with discrete types including selfish S-type and fairness-concerned F-type. The manufacturer can observe and thereby know the behavioral type of the retailer in the scenario of symmetric information, while it cannot in the scenario of asymmetric information. In the approach of game theory, the optimal carbon emission reducing strategy and pricing strategy in the symmetric scenario and asymmetric scenario are achieved successively. By comparing the above two scenarios, the impacts stemming from the asymmetric information of fairness concerns at the individual level and systematic level are analyzed, respectively. A case study is offered before concluding some implications for the supply chain management. The findings include the following: Firstly, the asymmetric information of fairness concerns enhances the carbon emission reduction significantly. Although the fairness concerns alone decrease the carbon emission reduction, the asymmetric information increases with the dominating power. Secondly, the asymmetric information of fairness concerns raises the wholesale price and retail price dramatically. Although the impact of either fairness concerns or asymmetric information randomly changes with the behavioral type and information structure, their interactive impacts are stable and change smoothly. Thirdly, the asymmetric information of fairness concerns promotes a fairer profit distribution, while either fairness concerns or asymmetric information alone hardly changes the overall profit of the low-carbon supply chain.
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Huo, Hong, Dan Luo, Zhanghua Yan, and Hao He. "Pricing Decisions in Dual-Channel Supply Chain considering Different Fairness Preferences and Low-Carbon Advertising Level." Discrete Dynamics in Nature and Society 2022 (September 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/4589681.

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Countries around the world advocate low-carbon, green, and environmentally friendly lifestyles to combat climate change, which provides clear direction for enterprise decisions. This paper studies a low-carbon dual-channel supply chain based on behavioral economics, incentive theory, and optimization models to better formulate pricing decisions. This paper constructs a fair and neutral decentralized decision-making model (FNDD), a decentralized decision-making model considering Nash bargaining fairness concerns (NBFDD), a decentralized decision-making model considering absolute fairness concerns (AFDD), and a fair and neutral centralized decision-making model (FNCD) considering consumer preferences and the situations where supply chain members are fairness concerns or fairness neutrality. This paper analyzes the effect of low-carbon advertising level on pricing strategies of online retailers and offline stores and compares pricing strategies of online retailers and offline stores in four decisions. The results show that Nash bargaining fairness concerns of supply chain members could effectively reduce the retail price of low-carbon products and increase their sales volumes. Absolute fairness concerns intensify the dual marginal effect of decentralized decision-making.
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Jiang, Wen, Linqing Pu, Ting Huang, Li Yuan, and Lu Gan. "The Effect of Fairness Concern on Carbon Emission Reduction and Revenue Distribution in Construction Supply Chain: Power Structure Perspective." Discrete Dynamics in Nature and Society 2021 (November 26, 2021): 1–20. http://dx.doi.org/10.1155/2021/8118220.

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This paper invested a two-echelon construction supply chain that consists of a general contractor and a subcontractor. This paper constructs the centralized model and the decentralized models, respectively, and studies the emission reduction and revenue distribution strategies of construction supply chain considering fairness concern and cap-and-trade. Numerical analysis is carried out to analyze the influence of cap-and-trade and fairness concern on the optimal decision and the maximum profit of construction supply chain. This paper shows that, under cap-and-trade policy, the centralized model has the best emission reduction effect and the highest supply chain profit without fairness concern, while the general contractor’s Stackelberg model has the best emission reduction effect and the highest supply chain profit with fairness concern. In the two scenarios, the Vertical Nash model is the most unfavorable to emission reduction, and it will also seriously damage the interests of enterprises. In practice, supply chain should choose the general contractor’s Stackelberg model and avoid the Vertical Nash model. Because fairness concern of the subcontractor will damage the supply chain profits and emission reduction performance, the general contractor shall try to select the subcontractor with lower fairness concern to avoid the loss of profit. Besides, enterprises should actively take measures to reduce fairness concern, such as enterprises signing the contract price confidentiality clause, which aims to reduce fairness concern of the subcontractor. The results of this paper can not only enrich the research content of construction supply chain management, but also provide references for the government to formulate emission reduction policies.
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Zhang, Chengwei, Xiaohong Li, Jing Hu, Zhiyong Feng, and Jiaojiao Song. "Formal Modeling and Analysis of Fairness Characterization of E-Commerce Protocols." Journal of Applied Mathematics 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/138370.

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In the past, fairness verification of exchanges between the traders in E-commerce was based on a common assumption, so-called nonrepudiation property, which says that if the parties involved can deny that they have received or sent some information, then the exchanging protocol is unfair. So, the nonrepudiation property is not a sufficient condition. In this paper, we formulate a new notion of fairness verification based on the strand space model and propose a method for fairness verification, which can potentially determine whether evidences have been forged in transactions. We first present an innovative formal approach not to depend on nonrepudiation, and then establish a relative trader model and extend the strand space model in accordance with traders’ behaviors of E-commerce. We present a case study to demonstrate the effectiveness of our verification method.
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Van Craen, Maarten, and Wesley G. Skogan. "Achieving Fairness in Policing." Police Quarterly 20, no. 1 (July 31, 2016): 3–23. http://dx.doi.org/10.1177/1098611116657818.

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Decades of research on public support for the police has documented the prominent role of procedural justice in shaping popular views of police legitimacy and the predisposition of citizens to comply and cooperate with them. However, much less attention has been given to the issue of how to get police officers to actually act in accord with its principles when they interact with the public. Reminders of the importance and the difficulty of fostering police legitimacy are not hard to come by, as witnessed in events in the United States during 2014 to 2015. This article addresses the hard, multifaceted issue of fostering procedural justice in the ranks. It theorizes and assesses the relationship between fair supervision and fair policing. The results of our study indicate that perceived internal procedural justice is directly related to support for external procedural justice (modeling thesis), and also indirectly, via trust in citizens.
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Ting, Chiu-Yao, and Tai-Kuei Yu. "Modeling patient perceptions of service recovery: The effects of perceived fairness on health center repatronage." Social Behavior and Personality: an international journal 38, no. 3 (April 1, 2010): 395–403. http://dx.doi.org/10.2224/sbp.2010.38.3.395.

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Repatronage intentions towards Taiwanese health centers that had received patient complaints and implemented service recovery were investigated. Valid samples (N = 168) were collected from the complaint behavior of patients resulting from their experiences of service failures in health centers. Results indicate that perceptions of distributive fairness and procedural fairness in health centers were related to repatronage intentions. In contrast, interactional fairness did not have the anticipated relationship with repatronage intentions. Consequently, health centers personnel should identify themselves with patients' concerns and take a caring and sympathetic attitude towards them so as to encourage people to revisit the health centers.
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Sohaib, Muhammad, Peng Hui, Umair Akram, Abdul Majeed, Zubair Akram, and Muhammad Bilal. "Understanding the Justice Fairness Effects on eWOM Communication in Social Media Environment." International Journal of Enterprise Information Systems 15, no. 1 (January 2019): 69–84. http://dx.doi.org/10.4018/ijeis.2019010104.

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This article integrates the trust and justice fairness to construct a model for investigating the motivations behind customers eWOM in social media environment, specifically WeChat. Using data from the online surveys of netizens in China, the proposed model was verified and validated by using the structure equation modeling (SEM) technique. The outcomes reveal that customer trust appear to be mostly driven by interactional fairness, which in turn effects satisfaction. Procedural fairness and interactional fairness impacts considerably positive on satisfaction. Trust and satisfaction have a direct positive effect on the eWOM. However, trust has indirect influence on eWOM through the satisfaction. Discussions provide the useful implications for managers and future directions.
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Dissertations / Theses on the topic "Fairness modeling"

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Hoblos, Jalaa. "Access Disparity Modeling and Fairness Provisioning in Multi-Hop Wireless Networks." Kent State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=kent1365703079.

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Li, Yunzhao. "Modeling, simulations, and experiments to balance performance and fairness in P2P file-sharing systems." Diss., Kansas State University, 2013. http://hdl.handle.net/2097/15319.

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Doctor of Philosophy
Department of Electrical and Computer Engineering
Don Gruenbacher
Caterina Scoglio
In this dissertation, we investigate research gaps still existing in P2P file-sharing systems: the necessity of fairness maintenance during the content information publishing/retrieving process, and the stranger policies on P2P fairness. First, through a wide range of measurements in the KAD network, we present the impact of a poorly designed incentive fairness policy on the performance of looking up content information. The KAD network, designed to help peers publish and retrieve sharing information, adopts a distributed hash table (DHT) technology and combines itself into the aMule/eMule P2P file-sharing network. We develop a distributed measurement framework that employs multiple test nodes running on the PlanetLab testbed. During the measurements, the routing tables of around 20,000 peers are crawled and analyzed. More than 3,000,000 pieces of source location information from the publishing tables of multiple peers are retrieved and contacted. Based on these measurements, we show that the routing table is well maintained, while the maintenance policy for the source-location-information publishing table is not well designed. Both the current maintenance schedule for the publishing table and the poor incentive policy on publishing peers eventually result in the low availability of the publishing table, which accordingly cause low lookup performance of the KAD network. Moreover, we propose three possible solutions to address these issues: the self-maintenance scheme with short period renewal interval, the chunk-based publishing/retrieving scheme, and the fairness scheme. Second, using both numerical analyses and agent-based simulations, we evaluate the impact of different stranger policies on system performance and fairness. We explore that the extremely restricting stranger policy brings the best fairness at a cost of performance degradation. The varying tendency of performance and fairness under different stranger policies are not consistent. A trade-off exists between controlling free-riding and maintaining system performance. Thus, P2P designers are required to tackle strangers carefully according to their individual design goals. We also show that BitTorrent prefers to maintain fairness with an extremely restricting stranger policy, while aMule/eMule’s fully rewarding stranger policy promotes free-riders’ benefit.
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Akter, Lutfa. "Modeling, forecasting and resource allocation in cognitive radio networks." Diss., Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/3892.

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Carman, Benjamin Andrew. "Repairing Redistricting: Using an Integer Linear Programming Model to Optimize Fairness in Congressional Districts." Ohio University Honors Tutorial College / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1619177994406176.

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Jdidi, Anis. "On the use of hierarchical modulation for resource allocation in OFDMA-based networks." Phd thesis, Institut National des Télécommunications, 2011. http://tel.archives-ouvertes.fr/tel-00698488.

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We investigate, in this thesis, the use of Hierarchical Modulation (HM), a physical layer technique that enables to exploit multiuser diversity, for resource allocation in OFDMA-based systems with and without use of relaying, so as to improve the system capacity. HM allows the sharing of the resources, namely subcarriers and power, between users of different radio conditions by sending an additional stream to a user with good radio conditions on a subcarrier that was initially allocated to carry an original stream to a user with lower radio conditions. And this, without affecting the original user's rate nor the total amount of power assigned to the shared subcarrier. In the literature, most of the works that consider the use of HM focus solely on the physical layer performance, notably in terms of the bit error rate. And this for a static user scenario,i.e., with a fixed number of users in the system, each with an infinite service duration. This configuration however does not reflect the real system behavior where the number of users is dynamic, i.e., the users come to the system at random time epochs and leave it after a finite duration, corresponding to the completion of their services. The study of the system at the flow-level, as opposed to the packet level, for a dynamic user configuration, enables us to investigate the realistic relationship between capacity and demand and to quantify several system-level performance metrics, such as mean transfer times and blocking rates, which are meaningful both to the user and the network operator/provider.
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Vergara, Alonso Ekhiotz Jon. "Energy Modelling and Fairness for Efficient Mobile Communication." Doctoral thesis, Linköpings universitet, Programvara och system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-124538.

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Energy consumption and its management have been clearly identified as a challenge in computing and communication system design, where energy economy is obviously of paramount importance for battery powered devices. This thesis addresses the energy efficiency of mobile communication at the user end in the context of cellular networks. We argue that energy efficiency starts by energy awareness and propose EnergyBox, a parametrised tool that enables accurate and repeatable energy quantification at the user end using real data traffic traces as input. EnergyBox offers an abstraction of the underlying states for operation of the wireless interfaces and allows to estimate the energy consumption for different operator settings and device characteristics. The tool is used throughout the thesis to quantify and reveal inefficient data communication patterns of widely used mobile applications. We consider two different perspectives in the search of energy-efficient solutions. From the application perspective, we show that systematically quantifying the energy consumption of design choices (e.g., communication patterns, protocols, and data formats) contributes to a significantly smaller energy footprint. From the system perspective, we devise a cross-layer solution that schedules packet transmissions based on the knowledge of the network parameters that impact the energy consumption of the handset. These attempts show that application level decisions require a better understanding of possible energy apportionment policies at system level. Finally, we study the generic problem of determining the contribution of an entity (e.g., application) to the total energy consumption of a given system (e.g., mobile device). We compare the state-of-the-art policies in terms of fairness leveraging cooperative game theory and analyse their required information and computational complexity. We show that providing incentives to reduce the total energy consumption of the system (as part of fairness) is tightly coupled to the policy selection. Our study provides guidelines to select an appropriate policy depending on the characteristics of the system.
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Zaibidi, Nerda Zura. "Modelling human fairness in cooperative games : a goal programming approach." Thesis, University of Portsmouth, 2012. https://researchportal.port.ac.uk/portal/en/theses/modelling-human-fairness-in-cooperative-games(4c3d0987-0edc-45be-9c4b-b1114df6bb3e).html.

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The issues of rationality in human behavior and fairness in cooperation have gained interest in various economic studies. In many prescriptive models of games, rationality of human decision makers implicitly assumes exchange-ability. This means that real people are assumed to adopt the beliefs of a player as expressed in the game when placed in the shoes of that particular player. However, it is a well debated topic in the literature that this modeling assumption is not in accordance to what behavioral economists have observed in some games played with real human subjects. Even when assuming the role of the same player in the game, different people think differently about the fairness of a particular outcome. People also view fairness as an essential ingredient of their decision making processes in games on cooperation. The aim of this research is to develop a new modeling approach to decision making in games on cooperation in which fairness is an important consideration. The satisficing and egilitarian philosophies on which weighted and Chebyshev Goal Programming (GP) rely, seem to offer an adequate and natural way for modeling human decision processes in at least the single-shot games of coordination that are investigated in this work. The solutions returned by the proposed GP approach aim to strike the right balance on several dimensions of con icting goals that are set by players themselves and that arise in the mental models these players have of other relevant players.
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Ebenhöh, Eva. "Modelling human behaviour in social dilemmas using attributes and heuristics." Doctoral thesis, 2007. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2007101719.

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A question concerning not only modellers but also practitioners is: Under what circumstances can mutual cooperation be established and maintained by a group of people facing a common pool dilemma" A step before this question of institutional influences there is need for a different way of modelling human behaviour that does not draw on the rational actor paradigm, because this kind of modelling needs to be able to integrate various deviations from this theory shown in economic experiments. We have chosen a new approach based on observations in form of laboratory and field observations of actual human behaviour. We model human decision making as using an adaptive toolbox following the notion of Gigerenzer. Humans draw on a number of simple heuristics that are meaningful in a certain situation but may be useless in another. This is incorporated into our agent-based model by having agents perceive their environment, draw on a pool of heuristics to choose an appropriate one and use that heuristic.Behavioural differences can be incorporated in two ways. First, each agent has a number of attributes that differ in values, for example there are more and less cooperative agents. The second behavioural difference lies in the way, in which heuristics are chosen. With this modelling approach we contribute to a new way of modelling human behaviour, which is simple enough to be included into morecomplex models while at the same time realistic enough to cover actual decision making processes of humans. Modellers should be able to use this approach without a need to get deep into psychological, sociological or economic theory. Stakeholders in social dilemmas, who may be confronted with such a model should understand, why an agent decides in the way it does.
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(6586319), LIna Abdulaziz Alfantoukh. "Multi-Stakeholder Consensus Decision-Making Framework Based on Trust and Risk." Thesis, 2019.

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This thesis combines human and machine intelligence for consensus decision-making, and it contains four interrelated research areas. Before presenting the four research areas, this thesis presents a literature review on decision-making using two criteria: trust and risk. The analysis involves studying the individual and the multi-stakeholder decision-making. Also, it explores the relationship between trust and risk to provide insight on how to apply them when making any decision. This thesis presents a grouping procedure of the existing trust-based multi-stakeholder decision-making schemes by considering the group decision-making process and models. In the first research area, this thesis presents the foundation of building multi-stakeholder consensus decision-making (MSCDM). This thesis describes trust-based multi-stakeholder decision-making for water allocation to help the participants select a solution that comes from the best model. Several criteria are involved when deciding on a solution such as trust, damage, and benefit. This thesis considers Jain's fairness index as an indicator of reaching balance or equality for the stakeholder's needs. The preferred scenario is when having a high trust, low damages and high benefits. The worst scenario involves having low trust, high damage, and low benefit. The model is dynamic by adapting to the changes over time. The decision to select is the solution that is fair for almost everyone. In the second research area, this thesis presents a MSCDM, which is a generic framework that coordinates the decision-making rounds among stakeholders based on their influence toward each other, as represented by the trust relationship among them. This thesis describes the MSCDM framework that helps to find a decision the stakeholders can agree upon. Reaching a consensus decision might require several rounds where stakeholders negotiate by rating each other. This thesis presents the results of implementing MSCDM and evaluates the effect of trust on the consensus achievement and the reduction in the number of rounds needed to reach the final decision. This thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in the stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the distance of the choices made by the stakeholders. Trust is useful in decreasing the distances. In the third research area, this thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the perturbation in the rating matrix. Trust is useful in increasing the rating matrix perturbation. Such perturbation helps to decrease the number of rounds. Therefore, trust helps to increase the speed of agreeing upon the same decision through the influence. In the fourth research area, this thesis presents Rating Aggregation operators in the implemented MSCDM framework. This thesis addresses the need for aggregating the stakeholders' ratings while they negotiate on the round of decisions to compute the consensus achievement. This thesis presents four aggregation operators: weighted sum (WS), weighted product (WP), weighted product similarity measure (WPSM), and weighted exponent similarity measure (WESM). This thesis studies the performance of those aggregation operators in terms of consensus achievement and the number of rounds needed. The consensus threshold controls the performance of these operators. The contribution of this thesis lays the foundation for developing a framework for MSCDM that facilitates reaching the consensus decision by accounting for the stakeholders' influences toward one another. Trust represents the influence.
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Books on the topic "Fairness modeling"

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Louisiana State University Agricultural Center. Workplace ethics: Lessons to strengthen character by modeling trustworthiness, respect, responsibility, fairness, caring and citizenship. [S.l., : Louisiana: Louisiana State University Agricultural Center, c1997]., 1997.

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Book chapters on the topic "Fairness modeling"

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Lavalle, Ana, Alejandro Maté, Juan Trujillo, and Jorge García-Carrasco. "Law Modeling for Fairness Requirements Elicitation in Artificial Intelligence Systems." In Conceptual Modeling, 423–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17995-2_30.

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Haffar, Rami, Ashneet Khandpur Singh, Josep Domingo-Ferrer, and Najeeb Jebreel. "Measuring Fairness in Machine Learning Models via Counterfactual Examples." In Modeling Decisions for Artificial Intelligence, 119–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13448-7_10.

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Mocanu, Irina, Lorina Negreanu, and Adina Magda Florea. "Agents Modeling under Fairness Assumption in Event-B." In Studies in Computational Intelligence, 301–7. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01571-2_35.

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Foulds, James R., Rashidul Islam, Kamrun Naher Keya, and Shimei Pan. "Bayesian Modeling of Intersectional Fairness: The Variance of Bias." In Proceedings of the 2020 SIAM International Conference on Data Mining, 424–32. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611976236.48.

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Wegner, Laila, Yana Houben, Martina Ziefle, and André Calero Valdez. "Fairness and the Need for Regulation of AI in Medicine, Teaching, and Recruiting." In Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. AI, Product and Service, 277–95. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77820-0_21.

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Chalmovianský, Pavel, and Bert Jüttler. "Fairness Criteria for Algebraic Curves." In Geometric Modelling, 41–51. Vienna: Springer Vienna, 2004. http://dx.doi.org/10.1007/978-3-7091-0587-0_4.

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Leith, Douglas J., and Robert Shorten. "Modelling TCP Throughput and Fairness." In Lecture Notes in Computer Science, 938–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24693-0_77.

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Hasselquist, David, Christoffer Lindström, Nikita Korzhitskii, Niklas Carlsson, and Andrei Gurtov. "QUIC Throughput and Fairness over Dual Connectivity." In Modelling, Analysis, and Simulation of Computer and Telecommunication Systems, 175–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68110-4_12.

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Murata, Tadao, and Manuel Silva. "Petri-Net-Based Fairness Concepts for Discrete Event Systems." In Realization and Modelling in System Theory, 549–57. Boston, MA: Birkhäuser Boston, 1990. http://dx.doi.org/10.1007/978-1-4612-3462-3_61.

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Gürcan, Önder. "Multi-Agent Modelling of Fairness for Users and Miners in Blockchains." In Communications in Computer and Information Science, 92–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24299-2_8.

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Conference papers on the topic "Fairness modeling"

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Zameshina, M., O. Teytaud, Fabien Teytaud, Vlad Hosu, Nathanael Carraz, Laurent Najman, and Markus Wagner. "Fairness in generative modeling." In GECCO '22: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3520304.3528992.

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Bonald, Thomas, and James Roberts. "Multi-Resource Fairness." In SIGMETRICS '15: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2745844.2745869.

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Zheng, Yong, Tanaya Dave, Neha Mishra, and Harshit Kumar. "Fairness In Reciprocal Recommendations." In UMAP '18: 26th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3213586.3226207.

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Ali, Zoraze, Biljana Bojovic, Lorenza Giupponi, and Josep Mangues Bafalluy. "On Fairness Evaluation." In MSWiM '16: 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2989250.2989255.

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Volk, Florian, Maria Pelevina, Sheikh Mahbub Habib, Sascha Hauke, and Max Muhlhauser. "Modeling Degrees of Fairness for Collaborations." In 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2014. http://dx.doi.org/10.1109/trustcom.2014.113.

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Venkateswaran, Sreekrishnan, and Santonu Sarkar. "Modeling Operational Fairness of Hybrid Cloud Brokerage." In 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). IEEE, 2018. http://dx.doi.org/10.1109/ccgrid.2018.00083.

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Giannopoulos, Giorgos, George Papastefanatos, Dimitris Sacharidis, and Kostas Stefanidis. "Interactivity, Fairness and Explanations in Recommendations." In UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3450614.3462238.

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Elahi, Mehdi, Himan Abdollahpouri, Masoud Mansoury, and Helma Torkamaan. "Beyond Algorithmic Fairness in Recommender Systems." In UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3450614.3461685.

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Im, Sungjin, Benjamin Moseley, Kamesh Munagala, and Kirk Pruhs. "Dynamic Weighted Fairness with Minimal Disruptions." In SIGMETRICS '20: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3393691.3394184.

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Kleinberg, Jon. "Inherent Trade-Offs in Algorithmic Fairness." In SIGMETRICS '18: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219617.3219634.

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