A Review for Unmanned Swarm Gaming: Framework, Model and Algorithm

The future of warfare will be the swarm, intelligent unmanned, and even systematic, but it hasn't been described in terms of a grouping confrontation. Specifically, due to the nature of the battlefield and the development trend of the future battlefield, swarm gaming is suitable. In this article, we investigated and concluded the attack defense problem for complex scenarios from game-theoretic a perspective. More than 60 key contributions are included in this survey, covering many aspects of unmanned swarm gaming research: modeling methods and algorithms of swarm gaming communication control, task allocation, resource management, and cooperative control. The consistency of existing research is summarized by examining performance characteristics. We provide each game-theoretic model's abstractly expressed bilevel programming problem and combed the potential applications for complex scenarios. Finally, we propose promising future directions to shed light on future opportunities and applications.

[1]  N. Sundararajan,et al.  Dynamic Resource Allocation With Decentralized Multi-Task Assignment Approach for Perimeter Defense Problem , 2022, IEEE Transactions on Aerospace and Electronic Systems.

[2]  M. Gamcová,et al.  A Reasonable Alternative System for Searching UAVs in the Local Area , 2022, Sensors.

[3]  Ziyang Zhen,et al.  Improved contract network protocol algorithm based cooperative target allocation of heterogeneous UAV swarm , 2021, Aerospace Science and Technology.

[4]  Shi Jin,et al.  Efficient Resource Allocation for Multi-UAV Communication Against Adjacent and Co-Channel Interference , 2021, IEEE Transactions on Vehicular Technology.

[5]  Gang Chen,et al.  The research on intelligent cooperative combat of UAV cluster with multi-agent reinforcement learning , 2021, Aerospace Systems.

[6]  Wenxiang Gao,et al.  Automatic task scheduling optimization and collision-free path planning for multi-areas problem , 2021, Intelligent Service Robotics.

[7]  Lu Zhang,et al.  Research on Collaborative and Confrontation of UAV Swarms Based on SAC-OD Rules , 2021, IMMS.

[8]  Hazim Shakhatreh,et al.  PSO-Based UAV Deployment and Dynamic Power Allocation for UAV-Enabled Uplink NOMA Network , 2021, Wirel. Commun. Mob. Comput..

[9]  Chunxiao Jiang,et al.  Multi-UAV Cooperative Target Tracking Based on Swarm Intelligence , 2021, ICC 2021 - IEEE International Conference on Communications.

[10]  Kenli Li,et al.  Multi-task allocation with an optimized quantum particle swarm method , 2020, Appl. Soft Comput..

[11]  L. Xiaohu,et al.  Research on Network Attack and Defense Situation Based on Game Theory Model and NetLogo Simulation , 2020 .

[12]  Li Da Xu,et al.  Crowd-Based Cooperative Task Allocation via Multicriteria Optimization and Decision-Making , 2020, IEEE Systems Journal.

[13]  Hua Wu,et al.  A cooperative interference resource allocation method based on improved firefly algorithm , 2020 .

[14]  Hao Xu,et al.  Mean Field Game and Decentralized Intelligent Adaptive Pursuit Evasion Strategy for Massive Multi-Agent System under Uncertain Environment , 2020, 2020 American Control Conference (ACC).

[15]  Jay Simon,et al.  Cybersecurity investments in the supply chain: Coordination and a strategic attacker , 2020, Eur. J. Oper. Res..

[16]  Jun Zhang,et al.  Cooperative task assignment of multi-UAV system , 2020 .

[17]  Siddharth Mayya,et al.  Adaptive Task Allocation for Heterogeneous Multi-Robot Teams with Evolving and Unknown Robot Capabilities , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

[18]  Marco A. Wehrmeister,et al.  Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles , 2020, Sensors.

[19]  Dimitri N. Mavris,et al.  Tradespace Exploration and Analysis Using Mission Effectiveness in Aircraft Conceptual Design , 2020 .

[20]  Wang Kun,et al.  UAV cooperative attack and route planning based on DPSO algorithm , 2019, Journal of Physics: Conference Series.

[21]  Gunasekaran Raja,et al.  Inter-UAV Collision Avoidance using Deep-Q-Learning in Flocking Environment , 2019, 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

[22]  Jing Zhang,et al.  Modeling a multi-target attacker-defender game with multiple attack types , 2019, Reliab. Eng. Syst. Saf..

[23]  Koichi Hori,et al.  UAV/UGV Autonomous Cooperation: UAV assists UGV to climb a cliff by attaching a tether , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[24]  Javier Del Ser,et al.  Weighted strategies to guide a multi-objective evolutionary algorithm for multi-UAV mission planning , 2019, Swarm Evol. Comput..

[25]  Eva Onaindia,et al.  Cooperative Multi-Agent Planning , 2017, ACM Comput. Surv..

[26]  Jie Li,et al.  Cooperative search of UAV swarm based on improved ant colony algorithm in uncertain environment , 2017, 2017 IEEE International Conference on Unmanned Systems (ICUS).

[27]  María Dolores Rodríguez-Moreno,et al.  Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms , 2017, Soft Comput..

[28]  Songyang Lao,et al.  Collision Avoidance for Cooperative UAVs With Optimized Artificial Potential Field Algorithm , 2017, IEEE Access.

[29]  Qiang Yang,et al.  A Survey on Multi-Task Learning , 2017, IEEE Transactions on Knowledge and Data Engineering.

[30]  Yue Li,et al.  Multi-UAVs formation flight control based on leader-follower pattern , 2017, 2017 36th Chinese Control Conference (CCC).

[31]  Rui Peng,et al.  Defense and attack of performance-sharing common bus systems , 2017, Eur. J. Oper. Res..

[32]  Jun Tang,et al.  Cooperative Multi-UAV Collision Avoidance Based on Distributed Dynamic Optimization and Causal Analysis , 2017 .

[33]  Sarvapali D. Ramchurn,et al.  Coordinating Human-UAV Teams in Disaster Response , 2016, IJCAI.

[34]  Xiaoxuan Hu,et al.  Hierarchical method of task assignment for multiple cooperating UAV teams , 2015 .

[35]  Pei Li,et al.  A predator-prey particle swarm optimization approach to multiple UCAV air combat modeled by dynamic game theory , 2015, IEEE/CAA Journal of Automatica Sinica.

[36]  Xiaojun Shan,et al.  Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender-attacker game , 2013, Eur. J. Oper. Res..

[37]  Boniface Kayode Alese,et al.  Modeling Attacker-Defender Interaction as a Zero-Sum Stochastic Game , 2013 .

[38]  Youdan Kim,et al.  Task Assignment of Multiple UAVs using MILP and GA , 2010 .

[39]  Calin Belta,et al.  Automatic Deployment of Distributed Teams of Robots From Temporal Logic Motion Specifications , 2010, IEEE Transactions on Robotics.

[40]  Michael P. Wellman Methods for Empirical Game-Theoretic Analysis , 2006, AAAI.

[41]  Michael P. Wellman,et al.  Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems , 2006, AAMAS 2006.

[42]  Debasish Ghose,et al.  Multiple UAV task allocation using negotiation , 2006, AAMAS '06.

[43]  Petter Ögren,et al.  Combining Path Planning and Target Assignment to Minimize Risk in SEAD Missions , 2005 .

[44]  Genshe Chen,et al.  Particle Swarm Optimization for Resource Allocation in UAV Cooperative Control , 2004 .

[45]  Marios M. Polycarpou,et al.  Cooperative real-time search and task allocation in UAV teams , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[46]  L. E. Parker,et al.  Current research in multirobot systems , 2003, Artificial Life and Robotics.

[47]  Wright-Patterson Afb,et al.  TASK ALLOCATION FOR WIDE AREA SEARCH MUNITIONS VIA NETWORK FLOW OPTIMIZATION , 2001 .

[48]  Wolfram Burgard,et al.  Collaborative multi-robot exploration , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[49]  O. Bagasra,et al.  Proceedings of the National Academy of Sciences , 1914, Science.

[50]  Jerome Bracken,et al.  Robustness of preallocated preferential defense with assumed attack size and perfect attacking and defending weapons. Final report , 1986 .

[51]  Bernhard Rinner,et al.  Communication and Coordination for Drone Networks , 2016, ADHOCNETS.

[52]  Xiaofeng Hu,et al.  Modeling of attacking and defending strategies in situations with intentional threats , 2012, ISCRAM.

[53]  Shen Lincheng Study on Dynamic Game Method with Incomplete Information in UAV Attack-Defends Campaign , 2009 .

[54]  Shen Jian-dong,et al.  Study on air formation to ground attack-defends decision making in fuzzy condition , 2007 .

[55]  Debasish Ghose,et al.  Team, Game, and Negotiation based Intelligent Autonomous UAV Task Allocation for Wide Area Applications , 2007, Innovations in Intelligent Machines.

[56]  Heinrich von Stackelberg,et al.  Stackelberg (Heinrich von) - The Theory of the Market Economy, translated from the German and with an introduction by Alan T. PEACOCK. , 1953 .

[57]  J. Nash Equilibrium Points in N-Person Games. , 1950, Proceedings of the National Academy of Sciences of the United States of America.

[58]  Walid Saad,et al.  Author manuscript, published in "IEEE Transactions on Wireless Communications (2009) Saad-ITransW-2009" A Distributed Coalition Formation Framework for Fair User Cooperation in Wireless Networks , 2022 .