Assessment of Aerial Combat Game via Optimization-Based Receding Horizon Control

Başpınar, Barış; Koyuncu, Emre

doi:10.1109/access.2020.2974792

Cited by 14 publications

(14 citation statements)

References 18 publications

(29 reference statements)

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“…The work of Başpınar, Barış et al [ 81 ] focuses on the modelling of air-to-air combat between two unmanned aerial vehicles (UAVs) using an optimization-based control and game-theoretic approach. In this work, vehicle motion is expressed in terms of specific variables and any trajectory planning for moving from one waypoint to another is solved by determining the smooth curves satisfying defined conditions in flat output space.…”

Section: Use Of Game Theory In Defence Science and Technology Applica...mentioning

confidence: 99%

“…In [ 81 ], the authors provide cost functions associated with the degree of being in tail-chase to the target based on aspect and bearing angles as well as the cost functions associated with generating a maximum score when the opponent is within some threshold of the optimum shooting range. The cost functions are multiplied together to create the total cost.…”

Section: Use Of Game Theory In Defence Science and Technology Applica...mentioning

confidence: 99%

See 1 more Smart Citation

Game Theory in Defence Applications: A Review

Rajagopalan

Skvortsov

et al. 2022

Sensors

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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.

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Section: Use Of Game Theory In Defence Science and Technology Applica...mentioning

confidence: 99%

Section: Use Of Game Theory In Defence Science and Technology Applica...mentioning

confidence: 99%

Game Theory in Defence Applications: A Review

Rajagopalan

Skvortsov

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Several algorithms and approaches have been applied to realize control systems that enable autonomous systems to execute complex missions [29][30][31][32][33][34][35]. For instance, an autonomous decision-making for unmanned combat aerial vehicles (UCAVs) using genetic fuzzy trees is presented by authors in [29].…”

Section: Related Workmentioning

confidence: 99%

“…A multi-agent-based training system for USVs was presented in [35] and a combat task for combat USVs was used to evaluate the system performance. Other methods such as optimizations and game theoretic approaches have been reported [31][32][33].…”

Section: Related Workmentioning

confidence: 99%

A Coordinated Air Defense Learning System Based on Immunized Classifier Systems

Nantogma

Ran

2021

Symmetry

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Autonomous (unmanned) combat systems will become an integral part of modern defense systems. However, limited operational capabilities, the need for coordination, and dynamic battlefield environments with the requirement of timeless in decision-making are peculiar difficulties to be solved in order to realize intelligent systems control. In this paper, we explore the application of the learning classifier system and Artificial Immune models for coordinated self-learning air defense systems. In particular, this paper presents a scheme that implements an autonomous cooperative threat evaluation and weapon assignment learning approach. Taking into account uncertainties in a successful interception, target characteristics, weapon type and characteristics, closed-loop coordinated behaviors, we adopt a hierarchical multi-agent approach to coordinate multiple combat platforms to achieve optimal performance. Based on the combined strengths of learning classifier and artificial immune-based algorithms, the proposed scheme consists of two categories of agents; a strategy generation agent inspired by learning classifier system, and strategy coordination inspired by Artificial Immune System mechanisms. An experiment in a realistic environment shows that the adopted hybrid approach can be used to learn weapon-target assignment for multiple unmanned combat systems to successfully defend against coordinated attacks. The presented results show the potential for hybrid approaches for an intelligent system enabling adaptable and collaborative systems.

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“…Zain et al suggested that SQP is an efficient way to solve the power allocation problem in PD-NOMA with the min-max objective function [14]. The SLSQP is a SQP algorithm that uses an equivalent least-squares problem formulation and is considered as a popular method to implement SQP [39], [40], [41] This section uses box-plots to show the results. Therefore, we provide a short note on comprehending the box plots as follows: (i) The lines in the middle of the boxes show the median of a data series; (ii) The lower and upper edges of the rectangle represent the Q1 and Q3 percentile of a data-series; (iii) The whiskers are small horizontal lines.…”

Section: Simulationsmentioning

confidence: 99%