Trust-Based Multi-stakeholder Decision Making in Water Allocation System

Lecture Notes in Networks and Systems

et al. 2021

Self Cite

We propose, for the first time, a trustworthy acceptance metric and its measurement methodology to evaluate the trustworthiness of AI-based systems used in decision making in Food Energy Water (FEW) management. The proposed metric is a significant step forward in the standardization process of AI systems. It is essential to standardize the AI systems' trustworthiness, but until now, the standardization efforts remain at the level of high-level principles. The measurement methodology of the proposed includes human experts in the loop, and it is based on our trust management system. Our metric captures and quantifies the system's transparent

Section: Related Workmentioning

confidence: 99%

Trustworthy Acceptance: A New Metric for Trustworthy Artificial Intelligence Used in Decision Making in Food–Energy–Water Sectors

Lecture Notes in Networks and Systems

et al. 2021

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“…Several uses of trust in decision making are the transactions over the internet [7], trust-based consumer decision making models for e-commerce [11], multi-stakeholder decision-making model for water allocation problem [1], and a generic framework for consensus reaching [2]. We proposed a DSS using our measurement theory-based trust management framework for the natural resource sharing problem in FEW [26].…”

Section: Trust and Its Applicationsmentioning

confidence: 99%

Trust-Based Game-Theoretical Decision Making for Food-Energy-Water Management

Lecture Notes in Networks and Systems

et al. 2019

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Decision making has been an essential aspect of the life of both individuals or organizations. We all have to face situations where we need to decide whether a daily one such as having coffee or tea in the breakfast or selecting a graduate school for Ph.D. The importance of a decision increases as the duration of the impact of its results and the number of people that are affected increases. Food-Energy-Water (FEW) is one of the fields where the impacts can stay for a long time and affect many people and areas. In this paper, we proposed a game theory-based approach for decision making among FEW actors sharing a finite amount of continuous resource where actors have different weights on their trust and the amount of share that they receive in their payoff functions. Then, we run simulations on scenarios utilizing a more realistic discrete solution set for actors. Results have shown that when actors place more weight on trust in their payoff function, they tend to propose fairer solutions that are closer to the consensus point. Also, they move towards that point faster compared to actors with low trust weight.

“…Trust also has a various area of usage in decision making such as decision of consumers in e-commerce [18], online transactions [13], water allocation problem of multiple stakeholders [1], and a generic consensus framework [2]. Also, we presented our work on decision support system for resource sharing [38], the influence of rating of ratings [35], a game theory approach [36], and the role of trust sensitivity [37].…”

Section: Introductionmentioning

confidence: 99%

Control Theoretical Modeling of Trust-Based Decision Making in Food-Energy-Water Management

Advances in Intelligent Systems and Computing

et al. 2020

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We propose a hybrid Human-Machine decision making to manage Food-Energy-Water resources. In our system trust among human actors during decision making is measured and managed. Furthermore, such trust is used to pressure human actors to chose among the solutions generated by algorithms that satisfy the community's preferred trade-offs among various objectives. We model the trust-based loops in decision making by using control theory. In this system, the feedback information is the trust pressure that actors receive from peers. Using control theory, we studied the dynamics of the trust of an actor. Then, we presented the modeling of the change of solution distances. In both scenarios, we also calculated the settling times and the stability using the transfer functions and their Z-transforms as the number of rounds to show whether and when the decision making is finalized.