An Overview on Game Theory Applications to Engineering

Sánchez-Soriano, Joaquı́n

doi:10.1142/s0219198913400197

Cited by 22 publications

(15 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Game theory has historically been used to model economics, political science, and social science problems; however, the field has a wide range of potential applications in biology, computer science, and other engineering disciplines [ Myerson , ; Sanchez‐Soriano , ]. Within the field of water resources engineering, a game theory approach can be used to characterize multi‐objective and multi‐decision maker problems to generate a more realistic simulation of stakeholder behavior [ Madani , ].…”

Section: Introductionmentioning

confidence: 99%

“…In other words, game theory provides a useful approach in realistically approximating interactions between water resources technology, human behavior, and the natural environment: a crucial component of the socio‐hydrological framework [ Sivapalan et al ., ]. Historically, cooperative game theory applications have been more common among water resources researchers than non‐cooperative applications [ Madani , ; Sanchez‐Soriano , ]. Several studies that have modeled water resource questions using both cooperative and non‐cooperative approaches have identified cooperative strategies as having more utility than non‐cooperative strategies [ Eleftheriadou and Mylopoulous , ; Schreider et al ., ; Yeo and Jung , ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A game theory analysis of green infrastructure stormwater management policies

William

Garg

Stillwell

2017

Water Resources Research

View full text Add to dashboard Cite

Green stormwater infrastructure has been demonstrated as an innovative water resources management approach that addresses multiple challenges facing urban environments. However, there is little consensus on what policy strategies can be used to best incentivize green infrastructure adoption by private landowners. Game theory, an analysis framework that has historically been under‐utilized within the context of stormwater management, is uniquely suited to address this policy question. We used a cooperative game theory framework to investigate the potential impacts of different policy strategies used to incentivize green infrastructure installation. The results indicate that municipal regulation leads to the greatest reduction in pollutant loading. However, the choice of the “best” regulatory approach will depend on a variety of different factors including politics and financial considerations. Large, downstream agents have a disproportionate share of bargaining power. Results also reveal that policy impacts are highly dependent on agents' spatial position within the stormwater network, leading to important questions of social equity and environmental justice.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A game theory analysis of green infrastructure stormwater management policies

William

Garg

Stillwell

2017

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…The theoretical game techniques have been quite successfully used in computer science [13][14][15][16] and other engineering disciplines [17,18]. 6 The literature on network formation is vast.…”

mentioning

confidence: 99%

Formation of Stable and Efficient Social Storage Cloud

Mane

Krishnamurthy

Ahuja

2019

Games

View full text Add to dashboard Cite

In this paper, we study the formation of endogenous social storage cloud in a dynamic setting, where rational agents build their data backup connections strategically. We propose a degree-distance-based utility model, which is a combination of benefit and cost functions. The benefit function of an agent captures the expected benefit that the agent obtains by placing its data on others’ storage devices, given the prevailing data loss rate in the network. The cost function of an agent captures the cost that the agent incurs to maintain links in the network. With this utility function, we analyze what network is likely to evolve when agents themselves decide with whom they want to form links and with whom they do not. Further, we analyze which networks are pairwise stable and efficient. We show that for the proposed utility function, there always exists a pairwise stable network, which is also efficient. We show that all pairwise stable networks are efficient, and hence, the price of anarchy is the best that is possible. We also study the effect of link addition and deletion between a pair of agents on their, and others’, closeness and storage availability.

show abstract

“…This approach leads to a broad analysis of multi-agent interactions, particularly those involving negotiation and coordination problems [8]. Other game-theoretical applications to engineering are reported in [9].From a game-theoretical perspective, it can be distinguished among three types of games: matrix games, continuous games, and differential/dynamic games (see "The relationship among matricial games, full-potential population games, and resource allocation problems"). In matrix games (that generally use the normal form), individuals play simultaneously and only once, and the decision is mainly based on a static terms.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

The Role of Population Games and Evolutionary Dynamics in Distributed Control Systems: The Advantages of Evolutionary Game Theory

et al. 2017

View full text Add to dashboard Cite

Recently, there has been an increasing interest in studying large-scale distributed systems in the control community. Efforts have been invested in developing several techniques wishing to address the main challenges found in this kind of problems, for instance, the amount of information to guarantee the proper operation of the system and the economic costs associated to the required communication structure. Moreover, another issue appears when there is a large amount of required data to control the system. The measuring and transmission processes, and the computation of the control inputs make closed-loop systems suffer from high computational burden.One way to overcome such problems is to consider the use of multi-agent systems framework, which may be cast in game-theoretical terms. Game theory studies interactions between self-interested agents. Particularly, this theory tackles with the problem of interaction between agents using different strategies that wish to maximize their welfares. For instance in [1], the authors provide connections between games, optimization, and learning for signal processing in networks. Other approaches in terms of learning and games can be found in [2]. In [3], distributed computation algorithms are developed based on generalized convex games that do not require full information, and where there is a dynamic change in terms of network topologies. Applications of game theory in control of optical networks and game-theoretic methods for smart grids are described in [4], [5], [6]. Another approach in game theoretical methods is to design protocols or mechanisms that possess some desirable properties [7]. This approach leads to a broad analysis of multi-agent interactions, particularly those involving negotiation and coordination problems [8]. Other game-theoretical applications to engineering are reported in [9].From a game-theoretical perspective, it can be distinguished among three types of games: matrix games, continuous games, and differential/dynamic games (see "The relationship among matricial games, full-potential population games, and resource allocation problems"). In matrix games (that generally use the normal form), individuals play simultaneously and only once, and the decision is mainly based on a static terms. In this case, players or agents are individually treated. Differently, in continuous games, players have infinitely many pure strategies [10], [11]. On the other hand, in dynamic games it is assumed that players can use some type of learning mechanism that allows them to adjust the actions taken based on their past decisions. Basically, it can be said that dynamic games are characterized by three main problems: i) how to model the environment where players interact; ii) how to model the objectives of players; and iii) how to specify the order in which the actions are taken and how much information each player possesses. In this case, it is assumed that there are interactions between large number of agents (which are usually unknown) [12].Among these dynamic game...

show abstract

An Overview on Game Theory Applications to Engineering

Cited by 22 publications

References 80 publications

A game theory analysis of green infrastructure stormwater management policies

A game theory analysis of green infrastructure stormwater management policies

Formation of Stable and Efficient Social Storage Cloud

The Role of Population Games and Evolutionary Dynamics in Distributed Control Systems: The Advantages of Evolutionary Game Theory

Contact Info

Product

Resources

About