Abstract
At present, business decision making is a crucial task in every enterprise as it allows to minimize risks and maximize benefits. For effective decision making, large corporations and enterprises need tools that will help them detect inefficient activities in their internal processes. This article presents a virtual organization of agents designed to detect risky situations and provide recommendations to the internal auditors of large corporations. Each agent within the virtual organization facilitates the interconnection of enterprises with the central decision node of the corporation. The core of the agent-based virtual organization consists of two agents: one that is specialized in detecting risky situations in all aspects of business enterprise and an advisor agent which communicates with the evaluator agents of the different departments of a business and provides decision support services. This paper presents a real-case scenario which includes small and medium enterprises, the results demonstrate the feasibility of the proposed architecture.
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References
Yañez, J.C., Borrajo, L., Corchado, J.M.: A case-based reasoning system for business internal control. In: Fourth International ICSC Symposium. Soft Computing and Intelligent Systems for Industry, Paisley, Scotland, United Kingdom, 26–29 June 2001
Mas, J., Ramió, C.: La Auditoría Operativa en la Práctica. Ed. Marcombo, Barcelona (1997)
Rodriguez, S., Julián, V., Bajo, J., Carrascosa, C., Botti, V., Corchado, J.M.: Agent-based virtual organization architecture. Eng. Appl. Artif. Intell. 24(5), 895–910 (2011)
Bajo, J., De Paz, Y., De Paz, J.F., Corchado, J.M.: Integrating case planning and RPTW neuronal networks to construct an intelligent environment for health care. Expert Syst. Appl. 36(3), 5844–5858 (2009)
García Coria, J.A., Castellanos-Garzón, J.A., Corchado, J.M.: Intelligent business processes composition based on multi-agent systems. Expert Syst. Appl. 41(4 Part 1), 1189–1205 (2014). https://doi.org/10.1016/j.eswa.2013.08.003
Tapia, D.I., Fraile, J.A., Rodríguez, S., Alonso, R.S., Corchado, J.M.: Integrating hardware agents into an enhanced multi-agent architecture for ambient intelligence systems. Inf. Sci. 222, 47–65 (2013). https://doi.org/10.1016/j.ins.2011.05.002
Costa, Â., Novais, P., Corchado, J.M., Neves, J.: Increased performance and better patient attendance in an hospital with the use of smart agendas. Log. J. IGPL 20(4), 689–698 (2012). https://doi.org/10.1093/jigpal/jzr021
García, E., Rodríguez, S., Martín, B., Zato, C., Pérez, B.: MISIA: middleware infrastructure to simulate intelligent agents. Adv. Intell. Soft Comput. 9, 107–116 (2011). https://doi.org/10.1007/978-3-642-19934-9_14
Rodríguez, S., De La Prieta, F., Tapia, D.I., Corchado, J.M.: Agents and computer vision for processing stereoscopic images. In: Corchado, E., Graña Romay, M., Manhaes Savio, A. (eds.) HAIS 2010. LNCS (LNAI, LNB), vol. 6077, pp. 93–100. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13803-4_12
Rodríguez, S., Gil, O., De La Prieta, F., Zato, C., Corchado, J.M., Vega, P., Francisco, M.: People detection and stereoscopic analysis using MAS. In: Proceedings of INES 2010 - 14th International Conference on Intelligent Engineering Systems (2010). https://doi.org/10.1109/INES.2010.5483855
Baruque, B., Corchado, E., Mata, A., Corchado, J.M.: A forecasting solution to the oil spill problem based on a hybrid intelligent system. Inf. Sci. 180(10), 2029–2043 (2010). https://doi.org/10.1016/j.ins.2009.12.032
Tapia, D.I., Corchado, J.M.: An ambient intelligence based multi-agent system for Alzheimer health care. Int. J. Ambient Comput. Intell. 1(1), 15–26 (2009). https://doi.org/10.4018/jaci.2009010102
Valanarasu, R., Christy, A.: Risk assessment and management in enterprise resource planning by advanced system engineering theory. Int. J. Bus. Intell. Data Min. 13(1–3), 3–14 (2018)
Namatame, A.: Agent-based modeling of economic instability. Stud. Comput. Intell. 753, 255–265 (2018)
Ai, J., Brockett, P.L., Wang, T.: Optimal enterprise risk management and decision making with shared and dependent risks. J. Risk Insur. 84(4), 1127–1169 (2017)
Callahan, C., Soileau, J.: Does enterprise risk management enhance operating performance? Adv. Account. 37, 122–139 (2017)
Raschke, R.L., Mann, A.: Enterprise content risk management: a conceptual framework for digital asset risk management. J. Emerg. Technol. Account. 14(1), 57–62 (2017)
Tapia, D.I., Rodríguez, S., Bajo, J., Corchado, J.M.: FUSION@, a SOA-based multi-agent architecture. Adv. Soft Comput. 50, 99–107 (2009)
Bremer, J., Lehnhoff, S.: Decentralized coalition formation with agent-based combinatorial heuristics. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. 6(3), 29–44 (2017)
Rodríguez, S., Pérez-Lancho, B., De Paz, J.F., Bajo, J., Corchado, J.M.: Ovamah: multi-agent-based adaptive virtual organizations, In: 12th International Conference on Information Fusion, FUSION 2009, pp. 990–997 (2009). https://ieeexplore.ieee.org/document/5203822/
Zato, C., Villarrubia, G., Sánchez, A., Barri, I., Rubión, E., Fernandez, A., Rebate, C., Cabo, J.A., Álamo, R., Sanz, J., Seco, J., Bajo, J., Corchado, J.M.: PANGEA - platform for automatic construction of organizations of intelligent agents. In: Advances in Intelligent and Soft Computing (AISC), vol. 151, pp. 229–239 (2012)
Bajo, J., Borrajo, M.L., De Paz, J.F., Corchado, J.M., Pellicer, M.A.: A multi-agent system for web-based risk management in small and medium business. Expert Syst. Appl. 39(8), 6921–6931 (2012)
Corchado, J.M., Pavón, J., Corchado, E.S., Castillo, L.F.: Development of CBR-BDI agents: a tourist guide application. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI, LNB), vol. 3155, pp. 547–559. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8
Laza, R., Pavon, R., Corchado, J.M.: A reasoning model for CBR_BDI agents using an adaptable fuzzy inference system. In: Conejo, R., Urretavizcaya, M., Pérez-de-la-Cruz, J.L. (eds.) TTIA 2003. LNCS (LNAI, LNB), vol. 3040, pp. 96–106. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-25945-9_10
Mata, A., Corchado, J.M.: Forecasting the probability of finding oil slicks using a CBR system. Expert Syst. Appl. 36(4), 8239–8246 (2009). https://doi.org/10.1016/j.eswa.2008.10.003
Glez-Peña, D., Díaz, F., Hernández, J.M., Corchado, J.M., Fdez-Riverola, F.: geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research. BMC Bioinform. 10, 187 (2009). https://doi.org/10.1186/1471-2105-10-187
Corchado, J.A., Aiken, J., Corchado, E.S., Lefevre, N., Smyth, T.: Quantifying the ocean’s CO2 budget with a CoHeL-IBR system. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS, vol. 3155, pp. 533–546. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8_39
Corchado, J.M., Borrajo, M.L., Pellicer, M.A., Yáñez, J.C.: Neuro-symbolic system for business internal control. In: Perner, P. (ed.) ICDM 2004. LNCS, vol. 3275, pp. 1–10. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30185-1_1
Fdez-Riverola, F., Corchado, J.M.: CBR based system for forecasting red tides. Knowl. Based Syst. 16(5–6 Spec), 321–328 (2003). https://doi.org/10.1016/S0950-7051(03)00034-0
Corchado, J.M., Aiken, J.: Hybrid artificial intelligence methods in oceanographic forecast models. IEEE Trans. Syst. Man Cybern. Part C-Appl. Rev. 32(4), 307–313 (2002). https://doi.org/10.1109/tsmcc.2002.806072
Fyfe, C., Corchado, J.: A comparison of kernel methods for instantiating case based reasoning systems. Adv. Eng. Inform. 16(3), 165–178 (2002). https://doi.org/10.1016/S1474-0346(02)00008-3
Fyfe, C., Corchado, J.M.: Automating the construction of CBR systems using kernel methods. Int. J. Intell. Syst. 16(4), 571–586 (2001). https://doi.org/10.1002/int.1024
Glez-Bedia, M., Corchado, J.M., Corchado, E.S., Fyfe, C.: Analytical model for constructing deliberative agents. Int. J. Eng. Intell. Syst. Electr. Eng. Commun. 10(3), 173–185 (2002)
Corchado, J.M., Corchado, E.S., Aiken, J., Fyfe, C., Fernandez, F., Gonzalez, M.: Maximum likelihood hebbian learning based retrieval method for CBR systems. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS (LNAI, LNB), vol. 2689, pp. 107–121. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-45006-8_11
Corchado, J.M., Fyfe, C.: Unsupervised neural method for temperature forecasting. Artif. Intell. Eng. 13(4), 351–357 (1999). https://doi.org/10.1016/S0954-1810(99)00007-2
Corchado, J., Fyfe, C., Lees, B.: Unsupervised learning for financial forecasting. In: Proceedings of the IEEE/IAFE/INFORMS 1998 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No. 98TH8367), pp. 259–263 (1998). https://doi.org/10.1109/CIFER.1998.690316
Corchado, E., MacDonald, D., Fyfe, C.: Optimal projections of high dimensional data. In: The 2002 IEEE International Conference on Data Mining, ICDM 2002, Maebashi TERRSA, Maebashi City, Japan, 9–12 December 2002. IEEE Computer Society (2002)
Fyfe, C., Corchado, E.: Maximum likelihood Hebbian rules. In: 10th European Symposium on Artificial Neural Networks, ESANN 2002, Bruges, 24–25–26 April 2002
Fyfe, C., Corchado E.: A new neural implementation of exploratory projection pursuit. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds.) IDEAL 2002. LNCS, vol. 2412, pp. 512–517. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45675-9_77
Fyfe, C., MacDonald, D.: ε-insensitive Hebbian learning. Neuro Comput. 47(1–4), 33–57 (2001)
Oja, E.: Neural networks, principal components and subspaces. Int. J. Neural Syst. 1, 61–68 (1989)
Oja, E., Ogawa, H., Wangviwattana, J.: Principal components analysis by homogeneous neural networks, part 1, the weighted subspace criterion. IEICE Trans. Inf. Syst. E75D, 366–375 (1992)
Dietterich, T.G.: Approximate statistical tests for comparing supervised classification learning algorithms. Neural Comput. 10(7), 1895–1923 (1998)
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This work has been funded by the Spanish Ministry of Science and Innovation (TIN2015-65515-C4-3-R).
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Borrajo, M.L., Corchado, J.M. (2018). An Agent-Based Virtual Organization for Risk Control in Large Enterprises. In: Uden, L., Hadzima, B., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2018. Communications in Computer and Information Science, vol 877. Springer, Cham. https://doi.org/10.1007/978-3-319-95204-8_24
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