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Volume 7 Issue 6
Oct.  2020

IEEE/CAA Journal of Automatica Sinica

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Haibin Zhu, "Group Multi-Role Assignment With Conflicting Roles and Agents," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1498-1510, Nov. 2020. doi: 10.1109/JAS.2020.1003354
Citation: Haibin Zhu, "Group Multi-Role Assignment With Conflicting Roles and Agents," IEEE/CAA J. Autom. Sinica, vol. 7, no. 6, pp. 1498-1510, Nov. 2020. doi: 10.1109/JAS.2020.1003354

Group Multi-Role Assignment With Conflicting Roles and Agents

doi: 10.1109/JAS.2020.1003354
Funds:  This work was supported in part by Natural Sciences and Engineering Research Council, Canada (NSERC) (RGPIN-2018-04818) and the funding from the Innovation for Defence Excellence and Security (IDEaS) Program from the Canadian Department of National Defence (DND)
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  • Group role assignment (GRA) is originally a complex problem in role-based collaboration (RBC). The solution to GRA provides modelling techniques for more complex problems. GRA with constraints (GRA+) is categorized as a class of complex assignment problems. At present, there are few generally efficient solutions to this category of problems. Each special problem case requires a specific solution. Group multi-role assignment (GMRA) and GRA with conflicting agents on roles (GRACAR) are two problem cases in GRA+. The contributions of this paper include: 1) The formalization of a new problem of GRA+, called group multi-role assignment with conflicting roles and agents (GMAC), which is an extension to the combination of GMRA and GRACAR; 2) A practical solution based on an optimization platform; 3) A sufficient condition, used in planning, for solving GMAC problems; and 4) A clear presentation of the benefits in avoiding conflicts when dealing with GMAC. The proposed methods are verified by experiments, simulations, proofs and analysis.

     

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  • [1]
    M. Bristow, L. P. Fang, and K. W. Hipel, “Agent-based modeling of competitive and cooperative behavior under conflict,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 44, no. 7, pp. 834–850, Jul. 2014. doi: 10.1109/TSMC.2013.2282314
    [2]
    T. Malsch and G. Weiss, “Conflicts in social theory and multi-agent systems: On importing sociological insights into distributed AI,” in Conflicting Agents: Conflict Management in Multi-Agent Systems, C. Tessier, L. Chaudron, and H. J. Müller, Eds. Boston, USA: Springer, 2002, pp. 111−149.
    [3]
    V. Rajan, A. Brutti, and A. Cavallaro, “Conflict NET: End-to-end learning for speech-based conflict intensity estimation,” IEEE Signal Process. Lett., vol. 26, no. 11, pp. 1668–1672, Nov. 2019. doi: 10.1109/LSP.2019.2944004
    [4]
    C. Tessier, H. J. Müller, H. Fiorino, and L. Chaudron, “Agents’ conflicts: New issues,” in Conflicting Agents: Conflict Management in Multi-Agent Systems, C. Tessier, L. Chaudron, and H. J. Mülle, Eds. Boston, USA: Springer, 2002, pp. 1−30.
    [5]
    H. B. Zhu and M. C. Zhou, “Role-based collaboration and its kernel mechanisms,” IEEE Trans. Syst.,Man,Cybern.,Part C, vol. 36, no. 4, pp. 578–589, Jul. 2006. doi: 10.1109/TSMCC.2006.875726
    [6]
    R. E. Burkard, M. Dell’Amico, and S. Martello, Assignment Problems, Revised Reprint. Philadelphia, USA: SIAM, 2009.
    [7]
    H. B. Zhu, M. C. Zhou, and R. Alkins, “Group role assignment via a Kuhn-Munkres algorithm-based solution,” IEEE Trans. Syst.,Man,Cybern.,Part A, vol. 42, no. 3, pp. 739–750, May 2012. doi: 10.1109/TSMCA.2011.2170414
    [8]
    H. B. Zhu, “Avoiding conflicts by group role assignment,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 46, no. 4, pp. 535–547, Apr. 2016. doi: 10.1109/TSMC.2015.2438690
    [9]
    H. B. Zhu, D. N. Liu, S. Q. Zhang, Y. Zhu, L. Y. Teng, and S. H. Teng, “Solving the many to many assignment problem by improving the Kuhn-Munkres algorithm with backtracking,” Theor. Comput. Sci., vol. 618, pp. 30–41, Mar. 2016. doi: 10.1016/j.tcs.2016.01.002
    [10]
    H. B. Zhu, D. N. Liu, S. Q. Zhang, S. H. Teng, and Y. Zhu, “Solving the group multirole assignment problem by improving the ILOG approach,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 47, no. 12, pp. 3418–3424, Dec. 2017. doi: 10.1109/TSMC.2016.2566680
    [11]
    H. B. Zhu, Y. Sheng, X. Z. Zhou, and Y. Zhu, “Group role assignment with cooperation and conflict factors,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 6, pp. 851–863, Jun. 2018. doi: 10.1109/TSMC.2016.2633244
    [12]
    D. N. Liu, Y. Y. Yuan, H. B. Zhu, S. H. Teng, and C. Q. Huang, “Balance preferences with performance in group role assignment,” IEEE Trans. Cybern., vol. 48, no. 6, pp. 1800–1813, Jun. 2018. doi: 10.1109/TCYB.2017.2715560
    [13]
    D. N. Liu, B. Y. Huang, and H. B. Zhu, “Solving the tree-structured task allocation problem via group multirole assignment,” IEEE Trans. Autom. Sci. Eng., vol. 17, no. 1, pp. 41–55, Jan. 2020. doi: 10.1109/TASE.2019.2908762
    [14]
    H. B. Zhu, “Maximizing group performance while minimizing budget,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 50, no. 2, pp. 633–645, Feb. 2020. doi: 10.1109/TSMC.2017.2735300
    [15]
    H. B. Zhu, “Avoiding critical members in a team by redundant assignment,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 50, no. 7, pp. 2729–2740, Jul. 2020.
    [16]
    H. B. Zhu and Y. Zhu, “Group role assignment with agents' busyness degrees,” in Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Banff, Canada, 2017, pp. 3201−3206.
    [17]
    H. B. Zhu and Y. Zhu, “Group role assignment with agents’ preferences,” in Proc. 14th IEEE Int. Conf. Networking, Sensing and Control, Calabria, Italy, 2017, pp. 605−610.
    [18]
    H. B. Zhu, “The most economical redundant assignment,” in Proc. IEEE Int. Conf. Systems, Man and Cybernetics, Bari, Italy, 2019, pp. 146−151.
    [19]
    R. L. Rardin, Optimization in Operations Research. Upper Saddle River, USA: Prentice Hall, 1997.
    [20]
    M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness. New York, USA: W. H. Freeman and Company, 1979.
    [21]
    H. W. Kuhn, “The Hungarian method for the assignment problem,” Nav. Res. Log., vol. 52, no. 1, pp. 7–21, Feb. 2005. doi: 10.1002/nav.20053
    [22]
    J. Munkres, “Algorithms for the assignment and transportation problems,” J. Soc. Ind. Appl. Math., vol. 5, no. 1, pp. 32–38, Mar. 1957. doi: 10.1137/0105003
    [23]
    C. H. Papadimitriou, “On the complexity of integer programming,” J. ACM, vol. 28, no. 4, pp. 765–768, Oct. 1981. doi: 10.1145/322276.322287
    [24]
    L. A. Wolsey and G. L. Nemhauser, Integer and Combinatorial Optimization. New York, USA: Wiley-Interscience, 1999.
    [25]
    IBM, “IBM ILOG CPLEX optimization studio,” [Online]. Available: http://www-01.ibm.com/software/integration/optimization/cplex-optimization-studio/
    [26]
    R. S. Pressman, Software Engineering: A Practitioner’s Approach. 6th ed. New York, USA: McGraw-Hill Higher Education, 2005.
    [27]
    Q. X. Cai, X. Z. Gao, and Y. Deng, “Pignistic belief transform: A new method of conflict measurement,” IEEE Access, vol. 8, pp. 15265–15272, Jan. 2020. doi: 10.1109/ACCESS.2020.2966821
    [28]
    B. Canbaz, B. Yannou, and P. A. Yvars, “Resolving design conflicts and evaluating solidarity in distributed design,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 44, no. 8, pp. 1044–1055, Aug. 2014. doi: 10.1109/TSMC.2013.2296275
    [29]
    K. M. Damiano-Teixeira, “Managing conflicting roles: A qualitative study with female faculty members,” J. Fam. Econ. Iss., vol. 27, no. 2, pp. 310–334, Jun. 2006. doi: 10.1007/s10834-006-9012-0
    [30]
    W. Q. Guo, W. M. Healy, and M. C. Zhou, “Impacts of 2.4-GHz ISM band interference on IEEE 802.15.4 wireless sensor network reliability in buildings,” IEEE Trans. Instrum. Meas., vol. 61, no. 9, pp. 2533–2544, Sept. 2012. doi: 10.1109/TIM.2012.2188349
    [31]
    Y. Hong, B. Choi, K. Lee, and Y. Kim, “Conflict management considering a smooth transition of aircraft into adjacent airspace,” IEEE Trans. Intell. Trans. Syst., vol. 17, no. 9, pp. 2490–2501, Sept. 2016. doi: 10.1109/TITS.2016.2519904
    [32]
    X. B. Jiang, W. H. Wang, and K. Bengler, “Intercultural analyses of time-to-collision in vehicle–pedestrian conflict on an urban midblock crosswalk,” IEEE Trans. Intell. Transp. Syst., vol. 16, no. 2, pp. 1048–1053, Apr. 2015.
    [33]
    C. Katrakazas, M. Quddus, and W. H. Chen, “A simulation study of predicting real-time conflict-prone traffic conditions,” IEEE Trans. Intell. Transp. Syst., vol. 19, no. 10, pp. 3196–3207, Oct. 2018. doi: 10.1109/TITS.2017.2769158
    [34]
    R. A. Kinsara, D. M. Kilgour, and K. W. Hipel, “Inverse approach to the graph model for conflict resolution,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 45, no. 5, pp. 734–742, May 2015. doi: 10.1109/TSMC.2014.2376473
    [35]
    M. Klein, “Supporting conflict resolution in cooperative design systems,” IEEE Trans. Syst.,Man,Cybern., vol. 21, no. 6, pp. 1379–1390, Dec. 1991. doi: 10.1109/21.135683
    [36]
    B. Lv, R. J. Sun, H. B. Zhang, H. Xu, and R. Yue, “Automatic vehicle-pedestrian conflict identification with trajectories of road users extracted from roadside LiDAR sensors using a rule-based method,” IEEE Access, vol. 7, pp. 161594–161606, Jul. 2019. doi: 10.1109/ACCESS.2019.2951763
    [37]
    M. Nyanchama and S. Osborn, “The role graph model and conflict of interest,” ACM Trans. Inform. Syst. Secur., vol. 2, no. 1, pp. 3–33, Feb. 1999. doi: 10.1145/300830.300832
    [38]
    J. M. Such and N. Criado, “Resolving multi-party privacy conflicts in social media,” IEEE Trans. Knowledge Data Eng., vol. 28, no. 7, pp. 1851–1863, Jul. 2016. doi: 10.1109/TKDE.2016.2539165
    [39]
    C. Tomlin, G. J. Pappas, and S. Sastry, “Conflict resolution for air traffic management: A study in multiagent hybrid systems,” IEEE Trans. Autom. Control, vol. 43, no. 4, pp. 509–521, Apr. 1998. doi: 10.1109/9.664154
    [40]
    J. Yang, X. Xu, D. Yin, Z. W. Ma, and L. C. Shen, “A space mapping based 0–1 linear model for onboard conflict resolution of heterogeneous unmanned aerial vehicles,” IEEE Trans. Veh. Technol., vol. 68, no. 8, pp. 7455–7465, Aug. 2019. doi: 10.1109/TVT.2019.2919737
    [41]
    H. G. Zhang, H. Luo, Z. Wang, Y. H. Liu, and Y. A. Liu, “Multi-robot cooperative task allocation with definite path-conflict-free handling,” IEEE Access, vol. 7, pp. 138495–138511, Sept. 2019. doi: 10.1109/ACCESS.2019.2942966
    [42]
    G. Thomas, “Facilitator, teacher, or leader? Managing conflicting roles in outdoor education” J. Exp. Educ., vol. 32, no. 3, pp. 239–254, May 2010.
    [43]
    J. H. Ye, Z. W. Li, K. Yi, and A. Al-Ahmari, “Mining resource community and resource role network from event logs,” IEEE Access, vol. 6, pp. 77685–77694, Nov. 2018. doi: 10.1109/ACCESS.2018.2883774
    [44]
    Q. T. Zeng, J. Liu, C. H. Zhou, C. Liu, and H. Duan, “A novel approach for business process similarity measure based on role relation network mining,” IEEE Access, vol. 8, pp. 60918–60928, Mar. 2020. doi: 10.1109/ACCESS.2020.2983114
    [45]
    N. Q. Wu and M. C. Zhou, “Modeling and deadlock control of automated guided vehicle systems,” IEEE/ASME Trans. Mech., vol. 9, no. 1, pp. 50–57, Mar. 2004. doi: 10.1109/TMECH.2004.823875
    [46]
    G. Fortino, W. Russo, C. Savaglio, W. M. Shen, and M. C. Zhou, “Agent-oriented cooperative smart objects: From IoT system design to implementation,” IEEE Trans. Syst.,Man,Cybern.:Syst., vol. 48, no. 11, pp. 1939–1956, Nov. 2018. doi: 10.1109/TSMC.2017.2780618
    [47]
    G. Fortino, A. Guerrieri, W. Russo, and C. Savaglio, “Towards a development methodology for smart object-oriented IoT systems: A metamodel approach,” in Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Hong Kong, China, 2015, pp. 1297−1302.
    [48]
    G. Fortino, A. Garro, and W. Russo, “An integrated approach for the development and validation of multi-agent systems,” Comput. Syst. Sci. Eng., vol. 20, no. 4, pp. 259–271, Jul. 2005.
    [49]
    S. M. M. Rahman, “Cyber-physical-social system between a humanoid robot and a virtual human through a shared platform for adaptive agent ecology,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 190–203, Jan. 2018. doi: 10.1109/JAS.2017.7510760
    [50]
    S. C. Gao, M. C. Zhou, Y. R. Wang, J. J. Cheng, H. Yachi, and J. H. Wang, “Dendritic neuron model with effective learning algorithms for classification, approximation, and prediction,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 2, pp. 601–614, Feb. 2019. doi: 10.1109/TNNLS.2018.2846646

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    Highlights

    • A new problem of Group Role Assignment with Constraints (GRA+), called Group Multi-role Assignment (GMRA) with Conflicting roles and agents (GMAC) is proposed and formalized.
    • A practical solution based on an optimization platform, i.e., IBM ILOG CPLEX Optimization Package is provided.
    • A sufficient condition, used in planning, for solving GMAC problems is proved.
    • The benefits of avoiding conflicts when dealing with GMAC are presented.

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