A Two-Dimensional Model for Game Theory Based Predictive Analytics

Karimi, Mirhossein Mousavi; Rahimi, Shahram

doi:10.1109/csci54926.2021.00036

Cited by 4 publications

(16 citation statements)

References 9 publications

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“…The players' positions along x-axis are represented in Figure 3. Our model forecasts the result to be 7.0 years, which is in line with the reported value of [4,11]. While the actual delay is 8.33, the obtained result demonstrates how well the proposed model works when used to solve one-dimensional issues.…”

Section: 1supporting

confidence: 83%

“…Future research could result in a more efficient offer selection method. If no player can make an offer to the other actors that is greater than a certain threshold, we consider that the equilibrium has been attained [11].…”

Section: Median Voter Positionmentioning

confidence: 99%

“…In this section, our earlier two-dimensional model [11] is explained followed by an extension to the formulation to provide a model for N-dimensional problems. Attempts have been made to avoid repeating similar formulation, and to discuss only formulation that are modified for the N-dimensional model.…”

Section: Model Extensionmentioning

confidence: 99%

“…Two-Dimensional Model. The capability attribute in our 2D model is similar to the 1D model; however, the desired position and salience are assigned along x and y-axes for each actor [11].…”

Section: Model Extensionmentioning

confidence: 99%

“…If bargaining problems were limited to a single issue or, more specifically, along one axis, the models discussed thus far could address the problem and forecast the outcome; however, negotiation problems are frequently multifaceted, necessitating that the parties involved to go through a wide range of topics while they bargain. In a recent work [11], we have proposed a two-dimensional model to address more complex problems involving multiple issues. In this paper, we have expanded this work to an N-dimensional space and modified some of our key formulations to include actors' salience as a weighting factor for better accuracy.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Multidimensional Game Theory–Based Group Decision Model for Predictive Analytics

Karimi

Rahimi

Nagahisarchoghaei

et al. 2022

Computational and Mathematical Methods

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An N-dimensional game theory–based model for multi-actor predictive analytics is presented in this article. The proposed model expands our previous work on two-dimensional group decision model for predictive analytics. The one-dimensional models are used for the problems where actors are interacting in a single issue space only. This is less than an ideal assumption since; in most cases, players’ strategies may depend on the dynamics of multiple issues when dealing with other players. In this work, the one-dimensional model is expanded to N-dimensional model by considering different positions, and separate salience values, across different axes for the players. The model predicts an outcome for a given problem by taking into account stakeholder’s positions in different dimensions and their conflicting perspectives. To illustrate the capability of the proposed model, three case studies have been presented.

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Section: 1supporting

confidence: 83%

Section: Median Voter Positionmentioning

confidence: 99%

Section: Model Extensionmentioning

confidence: 99%

“…Two-Dimensional Model. The capability attribute in our 2D model is similar to the 1D model; however, the desired position and salience are assigned along x and y-axes for each actor [11].…”

Section: Model Extensionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Multidimensional Game Theory–Based Group Decision Model for Predictive Analytics

Karimi

Rahimi

Nagahisarchoghaei

et al. 2022

Computational and Mathematical Methods

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Effects of the In Ovo and Dietary Supplementation of L-Ascorbic Acid on the Growth Performance, Inflammatory Response, and Eye L-Ascorbic Acid Concentrations in Ross 708 Broiler Chickens

Mousstaaid

Fatemi

Elliott

et al. 2022

Animals

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Effects of the dietary and in ovo administration of L-ascorbic acid (L-AA) on the performance, plasma nitric oxide, and eye L-AA concentrations of Ross 708 broilers were investigated. At 17 days of incubation, live embryonated hatching eggs were randomly assigned to a non-injected or sham-injected (100 μL of saline) control group, or a group injected with either 12 or 25 mg of L-AA suspended in 100 μL of saline. Chicks received a commercial diet with or without 200 mg/kg of supplemental L-AA and were randomly assigned to each of 6 replicate floor pens in each in ovo injection-dietary treatment combination. Weekly live performance variables through 14 days of post hatch age (doa) and the eye weights in both sexes at 0, 7, and 14 doa were determined. At 0 and 14 doa, plasma nitric oxide levels and eye L-AA concentrations of one bird of each sex in each pen were determined. Dietary supplemental L-AA decreased feed intake and growth between 0 and 7 doa, but from 8 to 14 doa; all birds fed supplemental L-AA had a lower feed conversion ratio. At 14 doa, male chicks had higher eye L-AA concentrations and lower plasma nitric oxide levels when treated in ovo with 12 mg of L-AA. In conclusion, dietary L-AA may be used to improve feed conversion in the second week of broiler post hatch growth. However, the in ovo administration of 12 mg of L-AA can increase male eye L-AA concentrations and is effective in reducing their general inflammatory response.

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An Empirical Survey on Explainable AI Technologies: Recent Trends, Use-Cases, and Categories from Technical and Application Perspectives

et al. 2023

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In a wide range of industries and academic fields, artificial intelligence is becoming increasingly prevalent. AI models are taking on more crucial decision-making tasks as they grow in popularity and performance. Although AI models, particularly machine learning models, are successful in research, they have numerous limitations and drawbacks in practice. Furthermore, due to the lack of transparency behind their behavior, users need more understanding of how these models make specific decisions, especially in complex state-of-the-art machine learning algorithms. Complex machine learning systems utilize less transparent algorithms, thereby exacerbating the problem. This survey analyzes the significance and evolution of explainable AI (XAI) research across various domains and applications. Throughout this study, a rich repository of explainability classifications and summaries has been developed, along with their applications and practical use cases. We believe this study will make it easier for researchers to understand all explainability methods and access their applications simultaneously.

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A Two-Dimensional Model for Game Theory Based Predictive Analytics

Cited by 4 publications

References 9 publications

A Multidimensional Game Theory–Based Group Decision Model for Predictive Analytics

A Multidimensional Game Theory–Based Group Decision Model for Predictive Analytics

Effects of the In Ovo and Dietary Supplementation of L-Ascorbic Acid on the Growth Performance, Inflammatory Response, and Eye L-Ascorbic Acid Concentrations in Ross 708 Broiler Chickens

An Empirical Survey on Explainable AI Technologies: Recent Trends, Use-Cases, and Categories from Technical and Application Perspectives

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