Adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game

doi:10.23919/JSEE.2023.000041

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (3): 598-614.doi: 10.23919/JSEE.2023.000041

• COMPLEX SYSTEMS THEORY AND PRACTICE • Previous Articles

Adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game

Minggang YU¹^,²(), Yanjie NIU¹^,*(), Xueda LIU¹(), Dongge ZHANG¹(), Peng ZHENG¹(), Ming HE¹(), Ling LUO¹()

¹ Institute of Command and Control Engineering, Army Engineering University of the PLA, Nanjing 210007, China
² Institute of Communication Engineering, Army Engineering University of the PLA, Nanjing 210007, China

Received:2022-08-29 Online:2023-06-15 Published:2023-06-30
Contact: Yanjie NIU E-mail:yuminggang8989@163.com;niuyanjie@126.com;834732360@qq.com;ZhangDongGeU@126.com;1203158631@163.qq.com;paper_review@126.com;717426015@qq.com
About author:
YU Minggang was born in 1986. He received his B.S. degree in the School of Information Engineering from Wuhan University of Technology in 2009, and M.S. and Ph.D. degrees in the School of Command and Control Engineering from Army Engineering University of the PLA in 2012 and 2016, respectively. Since 2020, he has been an associate professor with Army Engineering University of the PLA, Nanjing, China. His research interests are system of systems engineering and theory of intelligent command and control. E-mail: yuminggang8989@163.com

NIU Yanjie was born in 1979. She received her B.S. and M.S. degrees in the School of Command and Control Engineering from Army Engineering University of the PLA in 2001 and 2004, respectively. She is an associate professor of Institute of Command and Control Engineering, Army Engineering University of the PLA. Her research interest is military complex system analysis. E-mail: niuyanjie@126.com

LIU Xueda was born in 1990. He received his B.S. and M.S. degrees in the School of Command and Control Engineering from Army Engineering University of the PLA in 2014 and 2021, respectively. He is an electronics engineer. His research interest is UAV cluster command and control. E-mail: 834732360@qq.com

ZHANG Dongge was born in 1965. He received his B.S. degree from National University of Defense Technology in 1986, and M.S. degree from Army Engineering University of the PLA in 1993, respectively. He is currently a professor with Army Engineering University of the PLA. His research interests include analysis of military complex systems, situation awareness, and game theory. E-mail: ZhangDongGeU@126.com

ZHENG Peng was born in 1991. He received his B.S. degree from the Military Economic College in 2013, and M.S. degree from Army Engineering University of the PLA in 2022, respectively. He is an electronics engineer in Army Engineering University of the PLA. His research interests include operational and military organization and management analysis. E-mail: 1203158631@163.qq.com

HE Ming was born in 1978. He received his B.S., M.S., and Ph.D. degrees from Army Engineering University of the PLA in 2001, 2004 and 2008, respectively. He is currently a professor with Army Engineering University of the PLA. His research interest is unmanned command and control. E-mail: paper_review@126.com

LUO Ling was born in 1987. She received her B.S. and M.S. degrees from Army Engineering University of the PLA in 2010 and 2013, respectively. She is an associate professor of the Institute of Command and Control Engineering, Army Engineering University of the PLA. Her research interest is unmanned command and control.E-mail: 717426015@qq.com
Supported by:
This work was supported by the National Natural Science Foundation of China (71901217), and the Key Primary Research Project of Primary Strengthening Program (2020-JCJQ-ZD-007)

Abstract

Abstract:

Autonomous cooperation of unmanned swarms is the research focus on “new combat forces” and “disruptive technologies” in military fields. The mechanism design is the fundamental way to realize autonomous cooperation. Facing the realistic requirements of a swarm network dynamic adjustment under the background of high dynamics and strong confrontation and aiming at the optimization of the coordination level, an adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game is designed. This paper analyzes military requirements and proposes the basic framework of autonomous cooperation of unmanned swarms, including the emergence of swarm intelligence, information network construction and collaborative mechanism design. Then, based on the framework, the adaptive dynamic reconfiguration mechanism is discussed in detail from two aspects: topology dynamics and strategy dynamics. Next, the unmanned swarms’ community network is designed, and the network characteristics are analyzed. Moreover, the mechanism characteristics are analyzed by numerical simulation, focusing on the impact of key parameters, such as cost, benefit coefficient and adjustment rate on the level of swarm cooperation. Finally, the conclusion is made, which is expected to provide a theoretical reference and decision support for cooperative mode design and combat effectiveness generation of unmanned swarm operations.

Key words: unmanned swarm operation, autonomous collaboration, topology reconstruction, evolutionary game

Minggang YU, Yanjie NIU, Xueda LIU, Dongge ZHANG, Peng ZHENG, Ming HE, Ling LUO. Adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game[J]. Journal of Systems Engineering and Electronics, 2023, 34(3): 598-614.

Figures/Tables 10

Fig 1

Fig 2

Table 1

Fig 3

Fig 4

Fig 5

Fig 6

Fig 7

Fig 8

Fig 9

References 57

1	KARPOWICZ J Warfare use of unmanned aerial vehicles. Safety & Defense, 2021, 7 (2): 51- 64.
2	FAN J R, LI D G, LI R P, et al Analysis on MAV/UAV cooperative combat based on complex network. Defence Technology, 2020, 16 (1): 150- 157.
3	NOWAK M A, SIGMUND K Evolution of indirect reciprocity. Nature, 2005, 437 (6685): 1291- 1298.
4	LIEBERMAN E, HAUERT C, NOWAK M A Evolutionary dynamics on graphs. Nature, 2005, 433 (7023): 312- 316. doi: 10.1038/nature03204
5	NOWAK M A Five rules for the evolution of cooperation. Science, 2006, 314 (5805): 1560- 1563. doi: 10.1126/science.1133755
6	SMITH J M, PRICE G R The logic of animal conflict. Nature, 1973, 246 (5427): 15- 18. doi: 10.1038/246015a0
7	NOWAK M A, MAY R M Evolutionary games and spatial chaos. Nature, 1992, 359 (6398): 826- 829. doi: 10.1038/359826a0
8	NOWAK M A, MAY R M The spatial dilemmas of evolution. International Journal of Bifurcation Chaos, 1993, 3 (1): 35- 78. doi: 10.1142/S0218127493000040
9	HAUERT C, DE MONTE S, HOFBAUER J, et al Volunteering as red queen mechanism for cooperation in public goods games. Science, 2002, 296 (5570): 1129- 1132. doi: 10.1126/science.1070582
10	OHTSUKI H, HAUERT C, LIEBERMAN E, et al A simple rule for the evolution of cooperation on graphs and social networks. Nature, 2006, 441 (7092): 502- 505. doi: 10.1038/nature04605
11	FU F, NOWAK M A, HAUERT C Invasion and expansion of cooperators in lattice populations: prisoner’s dilemma vs. snowdrift games. Journal of Theoretical Biology, 2010, 266 (3): 358- 366.
12	NOWAK M A, TARNITA C E, ANTAL T, et al Evolutionary dynamics in structured populations. Philosophical Transactions of the Royal Society B, 2010, 365 (1537): 19- 30. doi: 10.1098/rstb.2009.0215
13	PENA J, WU B, ARRANZ J, et al Evolutionary games of multiplayer cooperation on graphs. PLOS Computational Biology, 2016, 12 (8): 1- 15.
14	JONES S L, LEIPONEN A, VASUDEVA G The evolution of cooperation in the face of conflict: evidence from the innovation ecosystem for mobile telecom standards development. Strategic Management Journal, 2021, 42 (4): 710- 740. doi: 10.1002/smj.3244
15	JOSEF T, ANDREAS P, KRISHNENDU C, et al Population structure determines the tradeoff between fixation probability and fixation time. Communications Biology, 2019, 2, 138- 145.
16	ALLEN B, LIPPNER G, NOWAK M A Evolutionary games on isothermal graphs. Nature Communications, 2019, 10 (1): 1- 9. doi: 10.1038/s41467-018-07882-8
17	SANTOS F C, SANTOS M D, PACHECO J M Social diversity promotes the emergence of cooperation in public goods games. Nature, 2008, 454 (7201): 213- 216. doi: 10.1038/nature06940
18	SANTOS F C, PACHECO J M Scale-free networks provide a unifying framework for the emergence of cooperation. Physical Review Letters, 2005, 95 (9): 098104. doi: 10.1103/PhysRevLett.95.098104
19	SANTOS F C, PACHECO J M A new route to the evolution of cooperation. Journal of Evolutionary Biology, 2006, 19 (3): 726- 733. doi: 10.1111/j.1420-9101.2005.01063.x
20	SANTOS F C, PACHECO J M, LENAERTS T Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proceedings of the National Academy of Sciences, 2006, 103 (9): 3490- 3494. doi: 10.1073/pnas.0508201103
21	SANTOS F C, RODRIGUES J F, PACHECO J M Graph topology plays a determinant role in the evolution of cooperation. Proceedings of the Royal Society B: Biological Sciences, 2006, 273 (1582): 51- 55. doi: 10.1098/rspb.2005.3272
22	ZHOU L, WU B, DU J M, et al Aspiration dynamics generate robust predictions in heterogeneous populations. Nature Communications, 2021, 12 (1): 1- 9. doi: 10.1038/s41467-020-20314-w
23	MAYER J, OBERMULLER M, DENK J, et al Snowdrift game induces pattern formation in systems of self-propelled particles. Physical Review E, 2021, 104 (4): 044408. doi: 10.1103/PhysRevE.104.044408
24	OGBO N B, ELRAGIG A, HAN T A Evolution of coordination in pairwise and multi-player interactions via prior commitments. Adaptive Behavior, 2022, 30 (3): 257- 277. doi: 10.1177/1059712321993166
25	WU B, ALTROCK P M, WANG L, et al Universality of weak selection. Physical Review E, 2010, 82 (4): 046106. doi: 10.1103/PhysRevE.82.046106
26	DU J M, WU B, ALTROCK P M, et al Aspiration dynamics of multi-player games in finite populations. Journal of the Royal Society Interface, 2014, 11 (94): 20140077. doi: 10.1098/rsif.2014.0077
27	GOVAERT A, RAMAZI P, CAO M Rationality, imitation, and rational imitation in spatial public goods games. IEEE Trans. on Control of Network Systems, 2021, 8 (3): 1324- 1335. doi: 10.1109/TCNS.2021.3065655
28	LEE K H, CHAN C H, HUI P M, et al Cooperation in N-person evolutionary snowdrift game in scale-free Barabasi–Albert networks. Physica A: Statistical Mechanics and its Applications, 2008, 387 (22): 5602- 5608. doi: 10.1016/j.physa.2008.05.045
29	LUO Q, LIU L J, CHEN X J. Evolutionary dynamics of cooperation in the N-person stag hunt game. Physica D: Nonlinear Phenomena, 2021, 424: 132943.
30	FENG Z, NIU W J Hybrid artificial neural network and cooperation search algorithm for nonlinear river flow time series forecasting in humid and semi-humid regions. Knowledge-Based Systems, 2021, 211, 106580. doi: 10.1016/j.knosys.2020.106580
31	TAN S L, LV J H. Games and evolutionary dynamics on complex networks. Beijing: Higher Education Press, 2019. (in Chinese)
32	TARNITA C E The ecology and evolution of social behavior in microbes. Journal of Experimental Biology, 2017, 220 (1): 18- 24. doi: 10.1242/jeb.145631
33	CARATTINI S, LEVIN S, TAVONI A Cooperation in the climate commons. Review of Environmental Economics and Policy, 2019, 13 (2): 227- 247. doi: 10.1093/reep/rez009
34	SU Q, ZHOU L, WANG L Evolutionary multiplayer games on graphs with edge diversity. PLoS Computational Biology, 2019, 15 (4): e1006947. doi: 10.1371/journal.pcbi.1006947
35	SU Q, LI A, WANG L, et al Spatial reciprocity in the evolution of cooperation. Proceedings of the Royal Society B: Biological Sciences, 2019, 286 (1900): 20190041. doi: 10.1098/rspb.2019.0041
36	YU M G, HE M, MA Z Y, et al. Cooperative evolution mechanism of unmanned swarmss within the framework of public goods game. Mathematical Problems in Engineering, 2020(1): 1−12.
37	YU M G, HE M, ZHANG D G, et al An approach to coordinated control of structured unmanned swarmss based on evolutionary game. Proc. of the 3rd IEEE International Conference on Unmanned Systems, 2020, 1- 13.
38	YU M G, CHEN J, HE M, et al. Cooperative mechanism of unmanned cluster in community network based on evolutionary game. Scientia Sinica Technologica, 2023, 53(2): 221−242.
39	YU M G, ZHANG D G, KANG K, et al Cooperative evolution mechanism of unmanned swarmss based on multi public goods evolutionary game. Systems Engineering and Electronics, 2020, 42 (12): 2787- 2794.
40	YU M G, HE M, ZHANG D G, et al Advantages of unmanned swarmss strategy based on multi-player public goods evolutionary game. Systems Engineering and Electronics, 2021, 43 (9): 2553- 2561.
41	YU M G, HE M, ZHANG D G, et al. Cooperative control method of structured unmanned cluster based on evolutionary game. Fire Control & Command Control, 2021, 46(10): 24−31. (in Chinese)
42	LIU X D, HE M, YU M G Cooperative application of UAV swarms based on evolutionary game. Journal of Command and Control, 2021, 7 (2): 167- 173.
43	FINLAN A. The shape of warfare to come: a Swedish perspective 2020–2045. Defense & Security Analysis, 2021, 37(4): 472−491.
44	DoD. Unmanned systems integrated roadmap FY2017-2042. Washington DC: Office of the Secretary of Defense, 2013.
45	HATANO Y, MESBAHI M Agreement over random networks. IEEE Trans. on Automatic Control, 2005, 50 (11): 1867- 1872. doi: 10.1109/TAC.2005.858670
46	LI C, MAINI P K An evolving network model with community structure. Journal of Physics A: Mathematical and General, 2005, 38 (45): 9741. doi: 10.1088/0305-4470/38/45/002
47	ZHANG J L, ZHU Y Y, CHEN Z Q Evolutionary game dynamics of multiagent systems on multiple community networks. IEEE Trans. on Systems, Man, and Cybernetics: Systems, 2020, 50 (11): 4513- 4529.
48	GAO Y, LI D S Consensus evaluation method of multi-ground-target threat for unmanned aerial vehicle swarm based on heterogeneous group decision making. Computers & Electrical Engineering, 2019, 74, 223- 232.
49	SZOLNOKI A, CHEN X Cooperation and competition between pair and multi-player social games in spatial populations. Scientific Reports, 2021, 11 (1): 1- 9. doi: 10.1038/s41598-020-79139-8
50	GARRO A, MUHLHUSER M, TUNDIS A, et al Intelligent agents: multi-agent systems. Encyclopedia of Bioinformatics and Computational Biology, 2019, 1, 315- 320.
51	HOLLAND J H. Hidden order: how adaptation builds complexity. USA: Arts & Licensing International Inc, 1995.
52	LI P P, KE J, LIN Z, et al Collaborative behavior in evolutionary snowdrift games with the unconditional imitation rule on regular lattices. Physical Review E, 2012, 85 (2): 021111. doi: 10.1103/PhysRevE.85.021111
53	TAYLOR P D, JONKRT L B Evolutionary stable strategies and game dynamics. Mathematical Biosciences, 1978, 40 (1/2): 145- 156. doi: 10.1016/0025-5564(78)90077-9
54	SZABO G, TOKE C Evolutionary prisoner’s dilemma game on a square lattice. Physical Review E, 1998, 58 (1): 69- 73.
55	ALBERT L B, REKA A, JEONG H. Mean-field theory for scale-free random networks. Physica A: Statistical Mechanics and its Applications, 1999, 272(1): 173−187.
56	TARNITA C E, OHTSUKI H, ANTAL T, et al. Strategy selection in structured populations. Journal of Theoretical Biology, 2009, 259(3): 570−581.
57	WANG X J, XIA K Extended average abundance function of multi-player snowdrift evolutionary game under aspiration driven rule. Systems Engineering—Theory & Practice, 2019, 39 (5): 1128- 1137.

Strategy of i	Number of collaborators in i’s neighbors
Strategy of i	k_i	···	$k_{i}^{C} $	···	1	0
C	$r{{c}_{o}}-{{c}_{o}} $	···	$r\left( k_{i}^{c}{{c}_{o}}+{{c}_{o}} \right)/\left( {{k}_{i}}+1 \right)-{{c}_{o}} $	···	$2r{{c}_{o}}/\left( {{k}_{i}}+1 \right)-{{c}_{o}} $	$r{{c}_{o}}/\left( {{k}_{i}}+1 \right)-{{c}_{o}} $
D	$r{{k}_{i}}{{c}_{o}}/\left( {{k}_{i}}+1 \right) $	···	$rk_{i}^{c}{{c}_{o}}/\left( {{k}_{i}}+1 \right) $	···	$r{{c}_{o}}/\left( {{k}_{i}}+1 \right) $	0

[1]	Ye MA, Tianqing CHANG, Wenhui FAN. A single-task and multi-decision evolutionary game model based on multi-agent reinforcement learning [J]. Journal of Systems Engineering and Electronics, 2021, 32(3): 642-657.
[2]	Ming ZHANG, Jianjun ZHU, Hehua WANG. Evolutionary game analysis of problem processing mechanism in new collaboration [J]. Journal of Systems Engineering and Electronics, 2021, 32(1): 136-150.
[3]	Zhou Min, Deng Feiqi & Wu Sai. Coordination game model of co-opetition relationship on cluster supply chains [J]. Journal of Systems Engineering and Electronics, 2008, 19(3): 499-506.

Adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

Share this article

Figures/Tables 10

References 57

Related Articles 3

Recommended Articles

Metrics

Comments