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  • Multi-agent management of integrated food-energy-water systems using stochastic games: from Nash equilibrium to the social optimum
Title: Multi-agent management of integrated food-energy-water systems using stochastic games: from Nash equilibrium to the social optimum
Abstract System-level integration and optimization of food-energy-water systems (FEWS) require coordination of multiple agencies and decision-makers and incorporating their interdependence. In general, such coordination might be hard to achieve. As a result, the literature on FEWS management either optimizes the operations for one sector (or one decision-maker), or models interdependence among the sectors without optimizing their operations. In this article, we develop a novel multi-agent management optimization approach that is able to incorporate stochasticity and uncertainty in the system’s dynamics and interdependence of the water and energy resources for food production. The proposed method is the first attempt to utilize fundamentals of decision and game theories to optimize operations of multi-agent FEWS. We specifically focus on differentiating between (1) cooperative decision optimization of the operations, where all decision-makers cooperate to achieve the best outcome for the whole system, the social optimum, and (2) non-cooperative decision-making of the agents, the Nash equilibrium. Illustrating with a real-world case study of FEWS in Ventura County, California, we show the difference between the cooperative and non-cooperative decision making in terms of long-term expected cost of managing the system. We further show how the extra costs associated with utilizing the renewable sources of water and energy could be incentivised, so that the non-cooperative solution (the Nash equilibrium) would naturally converge to the best outcome for the whole system (the social optimum).  more » « less
Award ID(s):
1739676
PAR ID:
10190987
Author(s) / Creator(s):
; ;
Publisher / Repository:
IOP Publishing
Date Published:
Journal Name:
Environmental Research Letters
Volume:
15
Issue:
9
ISSN:
1748-9326
Page Range / eLocation ID:
Article No. 0940a4
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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