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Alipour M M, Abdolhosseinzadeh M. A Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem. JSDP 2022; 19 (1) :87-100

URL: http://jsdp.rcisp.ac.ir/article-1-1084-en.html

URL: http://jsdp.rcisp.ac.ir/article-1-1084-en.html

Article number: 7

Type of Study: Research |
Subject:
Paper

Received: 2019/10/15 | Accepted: 2021/12/6 | Published: 2022/06/22 | ePublished: 2022/06/22

Received: 2019/10/15 | Accepted: 2021/12/6 | Published: 2022/06/22 | ePublished: 2022/06/22

1. [1] D. J. Watts and S. H. Strogatz, "Collective dynamics of 'small-world'networks," nature, vol. 393, no. 6684, pp. 440, 1998. [DOI:10.1038/30918] [PMID]

2. [2] S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, and D.-U. Hwang, "Complex networks: Structure and dynamics," Physics reports, vol. 424, no. 4-5, pp. 175-308, 2006. [DOI:10.1016/j.physrep.2005.10.009]

3. [3] M. E. Newman, "The structure and function of complex networks," SIAM review, vol. 45, no. 2, pp. 167-256, 2003. [DOI:10.1137/S003614450342480]

4. [4] S. Wasserman and K. Faust, Social network analysis: Methods and applications. Cambridge university press, 1994. [DOI:10.1017/CBO9780511815478]

5. [5] R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon, "Network motifs: simple building blocks of complex networks," Science, vol. 298, no. 5594, pp. 824-827, 2002. [DOI:10.1126/science.298.5594.824] [PMID]

6. [6] U. Brandes et al., "On modularity clustering," IEEE transactions on knowledge and data engineering, vol. 20, no. 2, pp. 172-188, 2007. [DOI:10.1109/TKDE.2007.190689]

7. [7] J. Liu, W. Zhong, and L. Jiao, "A multiagent evolutionary algorithm for combinatorial optimization problems," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 40, no. 1, pp. 229-240, 2009. [DOI:10.1109/TSMCB.2009.2025775] [PMID]

8. [8] J. Liu, W. Zhong, and L. Jiao, "A multiagent evolutionary algorithm for constraint satisfaction problems," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 36, no. 1, pp. 54-73, 2006. [DOI:10.1109/TSMCB.2005.852980] [PMID]

9. [9] M. M. Alipour and S. N. Razavi, "A new multiagent reinforcement learning algorithm to solve the symmetric traveling salesman problem," Multiagent and Grid Systems, vol. 11, no. 2, pp. 107-119, 2015. [DOI:10.3233/MGS-150232]

10. [10] M. M. Alipour, S. N. Razavi, M. R. F. Derakhshi, and M. A. Balafar, "A hybrid algorithm using a genetic algorithm and multiagent reinforcement learning heuristic to solve the traveling salesman problem," Neural Computing and Applications, pp. 1-17, 2017. [DOI:10.1007/s00521-017-2880-4]

11. [11] M. M. Alipour and M. Abdolhosseinzadeh, "A multiagent reinforcement learning algorithm to solve the maximum independent set problem," Multiagent and Grid Systems, vol. 16, no. 1, pp. 101-115, 2020. [DOI:10.3233/MGS-200323]

12. [12] M. E. Newman, "Modularity and community structure in networks," Proceedings of the national academy of sciences, vol. 103, no. 23, pp. 8577-8582, 2006. [DOI:10.1073/pnas.0601602103] [PMID] [PMCID]

13. [13] A. Clauset, M. E. Newman, and C. Moore, "Finding community structure in very large networks," Physical review E, vol. 70, no. 6, p. 066111, 2004. [DOI:10.1103/PhysRevE.70.066111] [PMID]

14. [14] J. M. Kumpula, J. Saramäki, K. Kaski, and J. Kertész, "Limited resolution and multiresolution methods in complex network community detection," Fluctuation and Noise Letters, vol. 7, no. 03, pp. L209-L214, 2007. [DOI:10.1142/S0219477507003854]

15. [15] S. Fortunato, "Community detection in graphs," Physics reports, vol. 486, no. 3-5, pp. 75-174, 2010. [DOI:10.1016/j.physrep.2009.11.002]

16. [16] L. Donetti and M. A. Munoz, "Detecting network communities: a new systematic and efficient algorithm," Journal of Statistical Mechanics: Theory and Experiment, vol. 2004, no. 10, pp. P10012, 2004. [DOI:10.1088/1742-5468/2004/10/P10012]

17. [17] M. Girvan and M. E. Newman, "Community structure in social and biological networks," Proceedings of the national academy of sciences, vol. 99, no. 12, pp. 7821-7826, 2002. [DOI:10.1073/pnas.122653799] [PMID] [PMCID]

18. [18] M. E. Newman and M. Girvan, "Finding and evaluating community structure in networks," Physical review E, vol. 69, no. 2, pp. 026113, 2004. [DOI:10.1103/PhysRevE.69.026113] [PMID]

19. [19] F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, "Defining and identifying communities in networks," Proceedings of the national academy of sciences, vol. 101, no. 9, pp. 2658-2663, 2004. [DOI:10.1073/pnas.0400054101] [PMID] [PMCID]

20. [20] L. Hagen and A. B. Kahng, "A new approach to effective circuit clustering," in ICCAD, 1992, vol. 92, pp. 422-427. [DOI:10.1109/ICCAD.1992.279334]

21. [21] P. De Meo, E. Ferrara, G. Fiumara, and A. Provetti, "Mixing local and global information for community detection in large networks," Journal of Computer and System Sciences, vol. 80, no. 1, pp. 72-87, 2014. [DOI:10.1016/j.jcss.2013.03.012]

22. [22] J. Cao, Z. Bu, Y. Wang, H. Yang, J. Jiang, and H.-J. Li, "Detecting prosumer-community groups in smart grids from the multiagent perspective," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 8, pp. 1652-1664, 2019. [DOI:10.1109/TSMC.2019.2899366]

23. [23] C.-K. Han, S.-F. Cheng, and P. Varakantham, "A Homophily-Free Community Detection Framework for Trajectories with Delayed Responses," in Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019: International Foundation for Autonomous Agents and Multiagent Systems, pp. 2003-2005.

24. [24] X. Feng and X. Yang, "Fast convergent average consensus of multiagent systems based on community detection algorithm," Advances in Difference Equations, vol. 2018, no. 1, pp. 1-13, 2018. [DOI:10.1186/s13662-018-1901-7]

25. [25] P. Pons and M. Latapy, "Computing communities in large networks using random walks," J. Graph Algorithms Appl., vol. 10, no. 2, pp. 191-218, 2006. [DOI:10.7155/jgaa.00124]

26. [26] P. Ronhovde and Z. Nussinov, "Multiresolution community detection for megascale networks by information-based replica correlations," Physical Review E, vol. 80, no. 1, p. 016109, 2009. [DOI:10.1103/PhysRevE.80.016109] [PMID]

27. [27] M. Zhou and J. Liu, "A memetic algorithm for enhancing the robustness of scale-free networks against malicious attacks," Physica A: Statistical Mechanics and its Applications, vol. 410, pp. 131-143, 2014. [DOI:10.1016/j.physa.2014.05.002]

28. [28] T. N. Bui and B. R. Moon, "Genetic algorithm and graph partitioning," IEEE Transactions on computers, vol. 45, no. 7, pp. 841-855, 1996. [DOI:10.1109/12.508322]

29. [29] M. Tasgin, A. Herdagdelen, and H. Bingol, "Community detection in complex networks using genetic algorithms," arXiv preprint arXiv:0711.0491, 2007.

30. [30] C. Pizzuti, "Ga-net: A genetic algorithm for community detection in social networks," in International conference on parallel problem solving from nature, 2008: Springer, pp. 1081-1090. [DOI:10.1007/978-3-540-87700-4_107]

31. [31] A. Gog, D. Dumitrescu, and B. Hirsbrunner, "Community detection in complex networks using collaborative evolutionary algorithms," in European Conference on Artificial Life, 2007: Springer, pp. 886-894. [DOI:10.1007/978-3-540-74913-4_89]

32. [32] M. Gong, B. Fu, L. Jiao, and H. Du, "Memetic algorithm for community detection in networks," Physical Review E, vol. 84, no. 5, p. 056101, 2011. [DOI:10.1103/PhysRevE.84.056101] [PMID]

33. [33] J. Liu, W. Zhong, H. A. Abbass, and D. G. Green, "Separated and overlapping community detection in complex networks using multiobjective evolutionary algorithms," in IEEE Congress on Evolutionary Computation, 2010: IEEE, pp. 1-7. [DOI:10.1109/CEC.2010.5586522]

34. [34] X. Liu and T. Murata, "Advanced modularity-specialized label propagation algorithm for detecting communities in networks," Physica A: Statistical Mechanics and its Applications, vol. 389, no. 7, pp. 1493-1500, 2010. [DOI:10.1016/j.physa.2009.12.019]

35. [35] J. Duch and A. Arenas, "Community detection in complex networks using extremal optimization," Physical review E, vol. 72, no. 2, p. 027104, 2005. [DOI:10.1103/PhysRevE.72.027104] [PMID]

36. [36] B. Yang and D.-Y. Liu, "Force-based incremental algorithm for mining community structure in dynamic network," Journal of Computer Science and Technology, vol. 21, no. 3, pp. 393-400, 2006. [DOI:10.1007/s11390-006-0393-1]

37. [37] I. Gunes and H. Bingol, "Community detection in complex networks using agents," arXiv preprint cs/0610129, 2006.

38. [38] Z. Li and J. Liu, "A multi-agent genetic algorithm for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, vol. 449, pp. 336-347, 2016. [DOI:10.1016/j.physa.2015.12.126]

39. [39] J. Huang, B. Yang, D. Jin, and Y. Yang, "Decentralized mining social network communities with agents," Mathematical and Computer Modelling, vol. 57, no. 11-12, pp. 2998-3008, 2013. [DOI:10.1016/j.mcm.2013.03.005]

40. [40] G. Palla, I. Derényi, I. Farkas, and T. Vicsek, "Uncovering the overlapping community structure of complex networks in nature and society," nature, vol. 435, no. 7043, p. 814, 2005. [DOI:10.1038/nature03607] [PMID]

41. [41] S. J. Russell and P. Norvig, Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited, 2016.

42. [42] R. S. Sutton and A. G. Barto, Reinforcement learning: An introduction. Cambridge: MIT press, 1998. [DOI:10.1109/TNN.1998.712192]

43. [43] L. P. Kaelbling, M. L. Littman, and A. W. Moore, "Reinforcement learning: A survey," Journal of Artificial Intelligence Research, vol. 4, pp. 237-285, 1996. [DOI:10.1613/jair.301]

44. [44] P. Stone and M. Veloso, " Multiagent systems: A survey from the machine learning perspective," Autonomous Robots, vol. 8, no. 3, pp. 345-383, 2000. [DOI:10.1023/A:1008942012299]

45. [45] S. Sen and G. Weiss, "Learning in multiagent systems," in Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, G. Weiss Ed.: MIT Press, 1999, ch. 6, pp. 259-298.

46. [46] R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction. MIT Press, 1998. [DOI:10.1109/TNN.1998.712192]

47. [47] I. S. Dhillon, Y. Guan, and B. Kulis, "Kernel k-means: spectral clustering and normalized cuts," in Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 2004: ACM, pp. 551-556. [DOI:10.1145/1014052.1014118] [PMID]

48. [48] J. Shi and J. Malik, "Normalized cuts and image segmentation," Departmental Papers (CIS), pp. 107, 2000.

49. [49] W. W. Zachary, "An information flow model for conflict and fission in small groups," Journal of anthropological research, vol. 33, no. 4, pp. 452-473, 1977. [DOI:10.1086/jar.33.4.3629752]

50. [50] D. Lusseau, K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, and S. M. Dawson, "The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations," Behavioral Ecology and Sociobiology, vol. 54, no. 4, pp. 396-405, 2003. [DOI:10.1007/s00265-003-0651-y]

51. [51] V. Krebs, "Books about us politics," unpublished, http://www.orgnet.com, 2004.

52. [52] A. Lancichinetti, S. Fortunato, and F. Radicchi, "Benchmark graphs for testing community detection algorithms," Physical review E, vol. 78, no. 4, p. 046110, 2008. [DOI:10.1103/PhysRevE.78.046110] [PMID]

53. [53] L. Danon, A. Diaz-Guilera, J. Duch, and A. Arenas, "Comparing community structure identification," Journal of Statistical Mechanics: Theory and Experiment, vol. 2005, no. 09, pp. P09008, 2005. [DOI:10.1088/1742-5468/2005/09/P09008]

54. [54] M. Tokic, F. Schwenker, and G. Palm, "Meta-learning of exploration and exploitation parameters with replacing eligibility traces," presented at the In IAPR International Workshop on Partially Supervised Learning (pp. 68-79). Springer Berlin Heidelberg, 2013, May. [DOI:10.1007/978-3-642-40705-5_7]

55. [55] K. Kobayashi, H. Mizoue, T. Kuremoto, and M. Obayashi, "A meta-learning method based on temporal difference error," presented at the In International Conference on Neural Information Processing (pp. 530-537). Springer Berlin Heidelberg, 2009, December. [DOI:10.1007/978-3-642-10677-4_60]

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