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CLC number: TP182

On-line Access: 2017-01-20

Received: 2016-10-09

Revision Accepted: 2016-12-23

Crosschecked: 2016-12-29

Cited: 1

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Citations:  Bibtex RefMan EndNote GB/T7714


Hao Fang


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Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.1 P.139-148


Coalition formation based on a task-oriented collaborative ability vector

Author(s):  Hao Fang, Shao-lei Lu, Jie Chen, Wen-jie Chen

Affiliation(s):  School of Automation, Beijing Institute of Technology, Beijing 100081, China; more

Corresponding email(s):   fangh@bit.edu.cn, lu_shaolei@126.com, chenjie@bit.edu.cn, chen.wenjie@163.com

Key Words:  Collaborative vector, Task allocation, Multi-agent system, Coalition formation, Artificial intelligence

Hao Fang, Shao-lei Lu, Jie Chen, Wen-jie Chen. Coalition formation based on a task-oriented collaborative ability vector[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 139-148.

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%T Coalition formation based on a task-oriented collaborative ability vector
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%A Jie Chen
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%DOI 10.1631/FITEE.1601608

T1 - Coalition formation based on a task-oriented collaborative ability vector
A1 - Hao Fang
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A1 - Wen-jie Chen
J0 - Frontiers of Information Technology & Electronic Engineering
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1601608

coalition formation is an important coordination problem in multi-agent systems, and a proper description of collaborative abilities for agents is the basic and key precondition in handling this problem. In this paper, a model of task-oriented collaborative abilities is established, where five task-oriented abilities are extracted to form a collaborative ability vector. A task demand vector is also described. In addition, a method of coalition formation with stochastic mechanism is proposed to reduce excessive competitions. An artificial intelligent algorithm is proposed to compensate for the difference between the expected and actual task requirements, which could improve the cognitive capabilities of agents for human commands. Simulations show the effectiveness of the proposed model and the distributed artificial intelligent algorithm.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]An, B., Shen, Z.Q., Miao, C.Y., et al., 2007. Algorithms for transitive dependence-based coalition formation. IEEE Trans. Ind. Inform., 3(3):234-245.

[2]Auer, S., Heitzig, J., Kornek, U., et al., 2015. The dynamics of coalition formation on complex networks. Sci. Rep., 5, Article 13386.

[3]Bonabeau, E., Sobkowski, A., Theraulaz, G., et al., 1997. Adaptive task allocation inspired by a model of division of labor in social insects. Proc. Biocomputing and Emergent Computation, p.36-45.

[4]Diao, X.H., Fang, Y.W., Xiao, B.S., et al., 2014. Task allocation in cooperative air combat based on multi-agent coalition. J. Beijing Univ. Aeronaut. Astronaut., 40(9):1268-1275 (in Chinese).

[5]Du, J.P., Zhou, L., Qu, P., et al., 2010. Task allocation in multi-agent systems with swarm intelligence of social insects. 6th Int. Conf. on Natural Computation, p.4322-4326.

[6]Gensollen, N., Becker, M., Gauthier, V., et al., 2015. Coalition formation algorithm of prosumers in a smart grid environment. IEEE Int. Conf. on Communications, p.5896-5902.

[7]Haque, M.A., Egerstedt, M., 2009. Coalition formation in multi-agent systems based on bottlenose dolphin alliances. American Control Conf., p.3280-3285.

[8]Haque, M., Egerstedt, M., Rahmani, A., 2013. Multilevel coalition formation strategy for suppression of enemy air defenses missions. J. Aerosp. Inform. Syst., 10(6):287-296.

[9]Ketchpel, S., 1994. Forming coalitions in the face of uncertain rewards. AAAI National Conf. on Artificial Intelligence, p.414-419.

[10]Li, D.Y., Du, Y., 2014. Artificial Intelligence with Uncertainty (2nd Ed.). National Defence Industry Press, Beijing (in Chinese).

[11]Lu, S.L., Fang, H., 2016. An improved distributed coalition formation algorithm in MAS. Contr. Dec., in press.

[12]Pan, Y.H., 2016. Heading toward artificial intelligence 2.0. Engineering, 2(4):409-413.

[13]Saaty, T.L., 1990. How to make a decision: the analytic hierarchy process. Eur. J. Oper. Res., 48(1):9-26.

[14]Saaty, T.L., 2008. Decision making with the analytic hierarchy process. Int. J. Serv. Sci., 1(1):83-98.

[15]Sandhlom, T.W., Lesser, V.R.T., 1997. Coalitions among computationally bounded agents. Artif. Intell., 94(1):99-137.

[16]Sellner, B., Heger, F.W., Hiatt, L.M., et al., 2006. Coordinated multi-agent teams and sliding autonomy for large-scale assembly. Proc. IEEE, 94(7):1425-1444.

[17]Shehory, O., Kraus, S., 1996. A kernel-oriented model for coalition-formation in general environments: implementation and results. AAAI/IAAI, p.134-140.

[18]Shehory, O., Kraus, S., 1998. Methods for task allocation via agent coalition formation. Artif. Intell., 101(1):165-200.

[19]Sichman, J.S., Conte, R., Demazeau, Y., et al., 1998. A social reasoning mechanism based on dependence networks. Proc. 11th European Conf. on Artificial Intelligence, p.416-420.

[20]Whitbrook, A., Meng, Q.G., Chung, P.W.H., 2015. A novel distributed scheduling algorithm for time-critical multi-agent systems. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, p.6451-6458.

[21]Ye, D.Y., Zhang, M.J., Sutanto, D., 2015. Decentralised dispatch of distributed energy resources in smart grids via multi-agent coalition formation. J. Parall. Distr. Comput., 83:30-43.

[22]Zhao, W.Q., Meng, Q.G., Chung, P.W.H., 2016. A heuristic distributed task allocation method for multivehicle multitask problems and its application to search and rescue scenario. IEEE Trans. Cybern., 46(4):902-915.

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