Literature DB >> 35161778

Game Theory in Defence Applications: A Review.

Edwin Ho1, Arvind Rajagopalan2, Alex Skvortsov3, Sanjeev Arulampalam3, Mahendra Piraveenan1.   

Abstract

This paper presents a succinct review of attempts in the literature to use game theory to model decision-making scenarios relevant to defence applications. Game theory has been proven as a very effective tool in modelling the decision-making processes of intelligent agents, entities, and players. It has been used to model scenarios from diverse fields such as economics, evolutionary biology, and computer science. In defence applications, there is often a need to model and predict the actions of hostile actors, and players who try to evade or out-smart each other. Modelling how the actions of competitive players shape the decision making of each other is the forte of game theory. In past decades, there have been several studies that applied different branches of game theory to model a range of defence-related scenarios. This paper provides a structured review of such attempts, and classifies existing literature in terms of the kind of warfare modelled, the types of games used, and the players involved. After careful selection, a total of 29 directly relevant papers are discussed and classified. In terms of the warfares modelled, we recognise that most papers that apply game theory in defence settings are concerned with Command and Control Warfare, and can be further classified into papers dealing with (i) Resource Allocation Warfare (ii) Information Warfare (iii) Weapons Control Warfare, and (iv) Adversary Monitoring Warfare. We also observe that most of the reviewed papers are concerned with sensing, tracking, and large sensor networks, and the studied problems have parallels in sensor network analysis in the civilian domain. In terms of the games used, we classify the reviewed papers into papers that use non-cooperative or cooperative games, simultaneous or sequential games, discrete or continuous games, and non-zero-sum or zero-sum games. Similarly, papers are also classified into two-player, three-player or multi-player game based papers. We also explore the nature of players and the construction of payoff functions in each scenario. Finally, we also identify gaps in literature where game theory could be fruitfully applied in scenarios hitherto unexplored using game theory. The presented analysis provides a concise summary of the state-of-the-art with regards to the use of game theory in defence applications and highlights the benefits and limitations of game theory in the considered scenarios.

Entities:  

Keywords:  aerial warfare; decision making; defence science; game theory; ground warfare; maritime warfare; sensing; tracking

Mesh:

Year:  2022        PMID: 35161778      PMCID: PMC8838118          DOI: 10.3390/s22031032

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  8 in total

1.  Equilibrium Points in N-Person Games.

Authors:  J F Nash
Journal:  Proc Natl Acad Sci U S A       Date:  1950-01       Impact factor: 11.205

2.  'Infotaxis' as a strategy for searching without gradients.

Authors:  Massimo Vergassola; Emmanuel Villermaux; Boris I Shraiman
Journal:  Nature       Date:  2007-01-25       Impact factor: 49.962

3.  A game theory approach to target tracking in sensor networks.

Authors:  Dongbing Gu
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2010-02-25

4.  A game theory based framework for assessing incentives for local area collaboration with an application to Scottish salmon farming.

Authors:  Alexander G Murray
Journal:  Prev Vet Med       Date:  2014-04-02       Impact factor: 2.670

Review 5.  Game theoretic modelling of infectious disease dynamics and intervention methods: a review.

Authors:  Sheryl L Chang; Mahendra Piraveenan; Philippa Pattison; Mikhail Prokopenko
Journal:  J Biol Dyn       Date:  2020-01-29       Impact factor: 2.179

6.  Network growth models: A behavioural basis for attachment proportional to fitness.

Authors:  Michael Bell; Supun Perera; Mahendrarajah Piraveenan; Michiel Bliemer; Tanya Latty; Chris Reid
Journal:  Sci Rep       Date:  2017-02-13       Impact factor: 4.379

7.  Intermittent Information-Driven Multi-Agent Area-Restricted Search.

Authors:  Branko Ristic; Alex Skvortsov
Journal:  Entropy (Basel)       Date:  2020-06-08       Impact factor: 2.524

8.  Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic.

Authors:  Mahendra Piraveenan; Shailendra Sawleshwarkar; Michael Walsh; Iryna Zablotska; Samit Bhattacharyya; Habib Hassan Farooqui; Tarun Bhatnagar; Anup Karan; Manoj Murhekar; Sanjay Zodpey; K S Mallikarjuna Rao; Philippa Pattison; Albert Zomaya; Matjaz Perc
Journal:  R Soc Open Sci       Date:  2021-06-09       Impact factor: 2.963

  8 in total
  1 in total

Review 1.  n-Player Stochastic Duel Game Model with Applied Deep Learning and Its Modern Implications.

Authors:  Manik Gupta; Bhisham Sharma; Akarsh Tripathi; Shashank Singh; Abhishek Bhola; Rajani Singh; Ashutosh Dhar Dwivedi
Journal:  Sensors (Basel)       Date:  2022-03-21       Impact factor: 3.576

  1 in total

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