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Games
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Real World Applications of Game Theory
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Real World Applications of Game Theory

A special issue of Games (ISSN 2073-4336).

Deadline for manuscript submissions: closed (24 March 2016) | Viewed by 48405

Special Issue Editors

Prof. Dr. Karl Tuyls

E-Mail Website
Guest Editor
Department of Computer Science, University of Liverpool, Liverpool L69 3BX, UK
Prof. Dr. Simon Parsons

E-Mail Website
Guest Editor
Department of Informatics, King’s College London, London, UK

Special Issue Information

Dear Colleagues,

Recent years have seen an increase in the use of game theoretic concepts and tools (e.g., equilibria, stability properties, replicator dynamics, etc.) for real world applications in areas as diverse as robotics, big data, financial markets, energy (smart grid), security, social welfare, and space applications. Therefore, we are excited to invite you to submit an original research paper for a Special Issue of Games devoted to the study of the application of such game theoretic principles to real world problems including, but not limited to, coordination in multi-robot systems (e.g., collision avoidance and patrolling), agent-based economics for auctions and markets (e.g., foreign exchange), security games, modelling and optimization in smart grids, and crowdsourcing.

We believe that this will be a great opportunity to further emphasize and trigger the powerful role that tools from Game Theory can play in a variety of practical applications. We envisage a fairly broad scope for this Special Issue, and we will consider all studies that report on the use or deployment of game theoretic and decision theoretic concepts in real world applications. The keywords below are merely indicative.

Prof. Dr. Karl Tuyls
Prof. Dr. Simon Parsons
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Games is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Security Games (applications such as boarder patrolling, wildlife preservation, etc.)
  • Multi-Agent Learning (Using game theoretic concepts for applications such as air traffic control, smart grids, auctions)
  • Robotics (Using GT for coordinating multi-robot systems, collision avoidance, etc.)
  • Financial and Energy Markets (e.g., distributed market mechanisms)
  • Learning and Optimization in Computer Games (e.g., Poker)

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

526 KiB  
Article
Simulating the Impact of Crossover Kidney Transplantation on the Nord Italia Transplant Program
by Monica Salvioli, Roberto Lucchetti and Rosanna Torelli
Games 2016, 7(4), 30; https://doi.org/10.3390/g7040030 - 20 Oct 2016
Cited by 1 | Viewed by 6931
Abstract
The increasing number of patients affected by chronic kidney disease makes it necessary to rely on living donors. However, a patient often cannot exploit her potential donor, due to blood or tissue incompatibility. Therefore, crossover transplantation programs have been developed in several countriesin [...] Read more.
The increasing number of patients affected by chronic kidney disease makes it necessary to rely on living donors. However, a patient often cannot exploit her potential donor, due to blood or tissue incompatibility. Therefore, crossover transplantation programs have been developed in several countriesin order to increase the number of people receiving a kidney from a living donor. After reviewing the essential medical facts needed for the subsequent results, we quickly introduce two known algorithms for crossover transplantation. Next, we consider a dataset provided by the Nord Italia Transplant program, and we apply the above algorithms in order to highlight the benefits of these efficient procedures. Full article
(This article belongs to the Special Issue Real World Applications of Game Theory)
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1047 KiB  
Article
Evolutionary Game between Commensal and Pathogenic Microbes in Intestinal Microbiota
by Amy Wu and David Ross
Games 2016, 7(3), 26; https://doi.org/10.3390/g7030026 - 12 Sep 2016
Cited by 7 | Viewed by 8916
Abstract
The human intestinal microbiota plays a fundamental role in host health and is associated with many diseases when the homeostasis is disturbed. Although recent achievements in metagenomic sequencing have begun to reveal the variety of microbial composition associated with healthy and disease states, [...] Read more.
The human intestinal microbiota plays a fundamental role in host health and is associated with many diseases when the homeostasis is disturbed. Although recent achievements in metagenomic sequencing have begun to reveal the variety of microbial composition associated with healthy and disease states, species-specific interactions and systematic dynamics still pose a great challenge to resolve the complexity of human microbiota. Using Clostridium difficile infection in human intestinal microbiota as an example, we apply evolutionary game theory to gain a fundamental understanding of the phenotypic variability and dynamic progression of microbiota. Here, microbiota dynamics are determined by the frequency-dependent fitness of each phenotypic population in the presence of the others. More specifically, the fitness is a function of phenotypic composition of the microbiota. We show how the phenotypic variability of microbiota can be explained by game theoretical approach. Knowledge of this study provides a new perspective in administrating antibiotic when dealing with pathogenic invasion. Instead of solely targeting to pathogens, therapies should aim at the whole ecosystem by reducing the fitness of pathogens compared to that of commensal microbes. In this case, the system will eradicate the pathogens by itself. Full article
(This article belongs to the Special Issue Real World Applications of Game Theory)
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547 KiB  
Article
Space Debris Removal: A Game Theoretic Analysis
by Richard Klima, Daan Bloembergen, Rahul Savani, Karl Tuyls, Daniel Hennes and Dario Izzo
Games 2016, 7(3), 20; https://doi.org/10.3390/g7030020 - 11 Aug 2016
Cited by 13 | Viewed by 13659
Abstract
We analyse active space debris removal efforts from a strategic, game-theoretical perspective. Space debris is non-manoeuvrable, human-made objects orbiting Earth, which pose a significant threat to operational spacecraft. Active debris removal missions have been considered and investigated by different space agencies with the [...] Read more.
We analyse active space debris removal efforts from a strategic, game-theoretical perspective. Space debris is non-manoeuvrable, human-made objects orbiting Earth, which pose a significant threat to operational spacecraft. Active debris removal missions have been considered and investigated by different space agencies with the goal to protect valuable assets present in strategic orbital environments. An active debris removal mission is costly, but has a positive effect for all satellites in the same orbital band. This leads to a dilemma: each agency is faced with the choice between the individually costly action of debris removal, which has a positive impact on all players; or wait and hope that others jump in and do the ‘dirty’ work. The risk of the latter action is that, if everyone waits, the joint outcome will be catastrophic, leading to what in game theory is referred to as the ‘tragedy of the commons’. We introduce and thoroughly analyse this dilemma using empirical game theory and a space debris simulator. We consider two- and three-player settings, investigate the strategic properties and equilibria of the game and find that the cost/benefit ratio of debris removal strongly affects the game dynamics. Full article
(This article belongs to the Special Issue Real World Applications of Game Theory)
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1196 KiB  
Article
Sharing the Costs of Complex Water Projects: Application to the West Delta Water Conservation and Irrigation Rehabilitation Project, Egypt
by Stefano Moretti, Fioravante Patrone, Ariel Dinar and Safwat Abdel-Dayem
Games 2016, 7(3), 18; https://doi.org/10.3390/g7030018 - 15 Jul 2016
Cited by 2 | Viewed by 7002
Abstract
Effective sharing mechanisms of joint costs among beneficiaries of a project are a fundamental requirement for the sustainability of the project. Projects that are heterogeneous both in terms of the landscape of the area under development or the participants (users) lead to a [...] Read more.
Effective sharing mechanisms of joint costs among beneficiaries of a project are a fundamental requirement for the sustainability of the project. Projects that are heterogeneous both in terms of the landscape of the area under development or the participants (users) lead to a more complicated set of allocation mechanisms than homogeneous projects. The analysis presented in this paper uses cooperative game theory to develop schemes for sharing costs and revenues from a project involving various beneficiaries in an equitable and fair way. The proposed approach is applied to the West Delta irrigation project. It sketches a differential two-part tariff that reproduces the allocation of total project costs using the Shapley Value, a well-known cooperative game allocation solution. The proposed differential tariff, applied to each land section in the project reflecting their landscape-related costs, contrasts the unified tariff that was proposed using the traditional methods in the project planning documents. Full article
(This article belongs to the Special Issue Real World Applications of Game Theory)
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1406 KiB  
Article
Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals
by Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha, Manish Jain, Ripple Goyal and Milind Tambe
Games 2016, 7(3), 15; https://doi.org/10.3390/g7030015 - 27 Jun 2016
Cited by 12 | Viewed by 9467
Abstract
Game theoretic approaches have recently been used to model the deterrence effect of patrol officers’ assignments on opportunistic crimes in urban areas. One major challenge in this domain is modeling the behavior of opportunistic criminals. Compared to strategic attackers (such as terrorists) who [...] Read more.
Game theoretic approaches have recently been used to model the deterrence effect of patrol officers’ assignments on opportunistic crimes in urban areas. One major challenge in this domain is modeling the behavior of opportunistic criminals. Compared to strategic attackers (such as terrorists) who execute a well-laid out plan, opportunistic criminals are less strategic in planning attacks and more flexible in executing well-laid plans based on their knowledge of patrol officers’ assignments. In this paper, we aim to design an optimal police patrolling strategy against opportunistic criminals in urban areas. Our approach is comprised by two major parts: learning a model of the opportunistic criminal (and how he or she responds to patrols) and then planning optimal patrols against this learned model. The planning part, by using information about how criminals responds to patrols, takes into account the strategic game interaction between the police and criminals. In more detail, first, we propose two categories of models for modeling opportunistic crimes. The first category of models learns the relationship between defender strategy and crime distribution as a Markov chain. The second category of models represents the interaction of criminals and patrol officers as a Dynamic Bayesian Network (DBN) with the number of criminals as the unobserved hidden states. To this end, we: (i) apply standard algorithms, such as Expectation Maximization (EM), to learn the parameters of the DBN; (ii) modify the DBN representation that allows for a compact representation of the model, resulting in better learning accuracy and the increased speed of learning of the EM algorithm when used for the modified DBN. These modifications exploit the structure of the problem and use independence assumptions to factorize the large joint probability distributions. Next, we propose an iterative learning and planning mechanism that periodically updates the adversary model. We demonstrate the efficiency of our learning algorithms by applying them to a real dataset of criminal activity obtained from the police department of the University of Southern California (USC) situated in Los Angeles, CA, USA. We project a significant reduction in crime rate using our planning strategy as compared to the actual strategy deployed by the police department. We also demonstrate the improvement in crime prevention in simulation when we use our iterative planning and learning mechanism when compared to just learning once and planning. Finally, we introduce a web-based software for recommending patrol strategies, which is currently deployed at USC. In the near future, our learning and planning algorithm is planned to be integrated with this software. This work was done in collaboration with the police department of USC. Full article
(This article belongs to the Special Issue Real World Applications of Game Theory)
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