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Encouraging the Recycling Process of Urban Waste by Means of Game Theory Techniques Using a Multi-agent Architecture

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Book cover Advances in Artificial Intelligence - IBERAMIA 2018 (IBERAMIA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11238))

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Abstract

The increase in population has caused the amount of waste generated in cities to increase, generally in large cities. It is necessary to develop solutions to reduce the amount of waste, and to be able to recycle most of it, avoiding wasting natural resources. Thanks to the treatment of these wastes, it is possible to obtain information to reduce costs and reduce the amount of waste generated, allowing a large quantity of them to be recycled. It is necessary to develop solutions to reduce the amount of waste, and to be able to recycle most of it, avoiding wasting natural resources. One of the main advantages of the Internet is its ability to connect people in remote locations and in real time. This has allowed the emergence of numerous collaborative applications, previously unthinkable, that are capable of solving traditional problems. This paper aims to address the problem of waste treatment by encouraging recycling among the different users involved in the system. This objective is approached from a perspective in which participants are rewarded for the amount they recycle, in order to encourage their participation and involvement in the recycling process. A framework that integrates gamification methodologies and multi-agent technology is presented with a case study demonstrating the benefits of the developed system. More specifically, a case study has been carried out simulating the functionality of this system by recreating the conditions of a real urban environment. The case study has made it possible to evaluate the effectiveness of the gamification system for citizen incentive in the recycling process.

This work has been supported by the Spanish Government throughthe project SURF (grant TIN2015-65515 -C4-3-R) and FEDER funds.

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References

  1. Briones, A.G., González, J.R., de Paz Santana, J.F.: A drug identification system for intoxicated drivers based on a systematic review. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 4(4), 83–101 (2015)

    Google Scholar 

  2. Chamoso, P., De la Prieta, F., De Paz, F., Corchado, J.M.: Swarm agent-based architecture suitable for internet of things and smartcities. In: Omatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence. AISC, vol. 373, pp. 21–29. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19638-1_3

    Chapter  Google Scholar 

  3. Costa, Â., Barberá, S.M.H., Cámara, J.P., Novais, P., Inglada, V.J.J.: Persuasion and recommendation system applied to a cognitive assistant. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 5(2), 89–99 (2016)

    Article  Google Scholar 

  4. De La Prieta, F., Navarro, M., García, J.A., González, R., Rodríguez, S.: Multi-agent system for controlling a cloud computing environment. In: Correia, L., Reis, L.P., Cascalho, J. (eds.) EPIA 2013. LNCS, vol. 8154, pp. 13–20. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40669-0_2

    Chapter  Google Scholar 

  5. Eurostat, Statistics Explained: Waste statistics (2018). http://ec.europa.eu/eurostat/statistics-explained/index.php/Waste_statistics. Accessed 19 Dec 2017

  6. García, Ó., Alonso, R.S., Prieto, J., Corchado, J.M.: Energy efficiency in public buildings through context-aware social computing. Sensors 17(4), 826 (2017)

    Article  Google Scholar 

  7. García, Ó., Alonso, R.S., Tapia, D.I., Corchado, J.M.: CAFCLA: a framework to design, develop, and deploy am I-based collaborative learning applications. In: Recent Advances in Ambient Intelligence and Context-Aware Computing, pp. 187–209. IGI Global (2015)

    Google Scholar 

  8. García, O., Chamoso, P., Prieto, J., Rodríguez, S., de la Prieta, F.: A serious game to reduce consumption in smart buildings. In: Bajo, J., et al. (eds.) PAAMS 2017. CCIS, vol. 722, pp. 481–493. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60285-1_41

    Chapter  Google Scholar 

  9. González Briones, A., Chamoso, P., Barriuso, A.L.: Review of the Main Security Problems with Multi-Agent Systems used in E-commerce Applications (2016)

    Article  Google Scholar 

  10. González, A., Ramos, J., De Paz, J.F., Corchado, J.M.: Obtaining relevant genes by analysis of expression arrays with a multi-agent system. In: Overbeek, R., Rocha, M., Fdez-Riverola, F., De Paz, J. (eds.) Practical Applications of Computational Biology and Bioinformatics. AISC, vol. 375, pp. 137–146. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19776-0_15

    Chapter  Google Scholar 

  11. González-Briones, A., Ramos, J., De Paz, J.F., Corchado, J.M.: Multi-agent system for obtaining relevant genes in expression analysis between young and older women with triple negative breast cancer. J. Integr. Bioinform. 12(4), 1–14 (2015)

    Article  Google Scholar 

  12. González-Briones, A., Villarrubia, G., De Paz, J.F., Corchado, J.M.: A multi-agent system for the classification of gender and age from images. Comput. Vis. Image Underst. (2018). https://doi.org/10.1016/j.cviu.2018.01.012

  13. Meng, X., Wen, Z., Qian, Y.: Multi-agent based simulation for household solid waste recycling behavior. Resour. Conserv. Recycl. 128, 535–545 (2018)

    Article  Google Scholar 

  14. Mishra, N., Kumar, V., Chan, F.T.: A multi-agent architecture for reverse logistics in a green supply chain. Int. J. Prod. Res. 50(9), 2396–2406 (2012)

    Article  Google Scholar 

  15. Oliveira, T., Neves, J., Novais, P.: Guideline formalization and knowledge representation for clinical decision support. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 1(2), 1–11 (2012)

    Google Scholar 

  16. Prieto, J., Mazuelas, S., Bahillo, A., Fernández, P., Lorenzo, R.M., Abril, E.J.: On the minimization of different sources of error for an RTT-based indoor localization system without any calibration stage. In: 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6 (2010)

    Google Scholar 

  17. Rodríguez, S., de Paz, Y., Bajo, J., Corchado, J.M.: Social-based planning model for multiagent systems. Expert Syst. Appl. 38(10), 13005–13023 (2011)

    Article  Google Scholar 

  18. Román, J.A., Rodríguez, S., de la Prieta, F.: Improving the distribution of services in MAS. In: Bajo, J., et al. (eds.) PAAMS 2016. CCIS, vol. 616, pp. 37–46. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39387-2_4

    Chapter  Google Scholar 

  19. Silva, A., Oliveira, T., Neves, J., Novais, P.: Treating colon cancer survivability prediction as a classification problem. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 5(1), 37–50 (2016)

    Article  Google Scholar 

  20. Silveira, R.A., Comarella, R.L., Campos, R.L.R., Vian, J., de la Prieta, F.: Learning objects recommendation system: issues and approaches for retrieving, indexing and recomend learning objects. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 4(4), 69–82 (2015)

    Google Scholar 

  21. Silveira, R.A., da Silva Bitencourt, G.K., Gelaim, T.Â., Marchi, J., de la Prieta, F.: Towards a model of open and reliable cognitive multiagent systems: dealing with trust and emotions. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 4(3), 57–86 (2015)

    Article  Google Scholar 

  22. Tapia, D.I., Alonso, R.S., De Paz, J.F., Corchado, J.M.: Introducing a distributed architecture for heterogeneous wireless sensor networks. In: Omatu, S., et al. (eds.) IWANN 2009. LNCS, vol. 5518, pp. 116–123. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02481-8_16

    Chapter  Google Scholar 

  23. 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. The European Container Glass Federation (2017). FEVE PR recycling 2013. http://feve.org/wp-content/uploads/2016/04/Press-Release-EU.pdf. Accessed 19 Dec 2017

    Article  Google Scholar 

  24. Wood woRking INdustry RecycliNG (2017). Waste statistics. https://ec.europa.eu/growth/tools-databases/eip-raw-materials/en/content/wood-working-industry-recycling. Accessed 19 Dec 2017

  25. González-Briones, A., Prieto, J., Corchado, J.M., Demazeau, Y.: EnerVMAS: virtual agent organizations to optimize energy consumption using intelligent temperature calibration. In: de Cos Juez, F., et al. (eds.) HAIS 2018. LNCS, vol. 10870, pp. 387–398. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92639-1_32

    Chapter  Google Scholar 

  26. González-Briones, A., Chamoso, P., De La Prieta, F., Demazeau, Y., Corchado, J.M.: Agreement technologies for energy optimization at home. Sensors 18(5), 1633 (2018)

    Article  Google Scholar 

  27. González-Briones, A., De La Prieta, F., Mohamad, M.S., Omatu, S., Corchado, J.M.: Multi-agent systems applications in energy optimization problems: a state-of-the-art review. Energies 2018, 11 (1928)

    Google Scholar 

  28. González-Briones, A., Rivas, A., Chamoso, P., Casado-Vara, R., Corchado, J.M.: Case-based reasoning and agent based job offer recommender system. In: Graña, M., et al. (eds.) SOCO 18-CISIS 18-ICEUTE 18 2018. AISC, vol. 771, pp. 21–33. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94120-2_3

    Chapter  Google Scholar 

  29. Rivas, A., et al.: Semantic analysis system for industry 4.0. In: Uden, L., Hadzima, B., Ting, I.-H. (eds.) KMO 2018. CCIS, vol. 877, pp. 537–548. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95204-8_45

    Chapter  Google Scholar 

  30. Briones, A.G., et al.: Use of gamification techniques to encourage garbage recycling. a smart city approach. In: Uden, L., Hadzima, B., Ting, I.-H. (eds.) KMO 2018. CCIS, vol. 877, pp. 674–685. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95204-8_56

    Chapter  Google Scholar 

  31. Candanedo, I.S., Nieves, E.H., González, S.R., Martín, M.T.S., Briones, A.G.: Machine learning predictive model for industry 4.0. In: Uden, L., Hadzima, B., Ting, I.-H. (eds.) KMO 2018. CCIS, vol. 877, pp. 501–510. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95204-8_42

    Chapter  Google Scholar 

  32. González-Briones, A., et al.: GarbMAS: simulation of the application of gamification techniques to increase the amount of recycled waste through a multi-agent system. In: De La Prieta, F., Omatu, S., Fernández-Caballero, A. (eds.) DCAI 2018. AISC, vol. 800, pp. 332–343. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94649-8_40

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+i, 37007, Salamanca, Spain

    Alfonso González-Briones, Pablo Chamoso, Sara Rodríguez, Angélica González-Arrieta & Juan M. Corchado

  2. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka, 535-8585, Japan

    Juan M. Corchado

  3. Pusat Komputeran dan Informatik, Universiti Malaysia Kelantan, Karung Berkunci 36, Pengkaan Chepa, 16100, Kota Bharu, Kelantan, Malaysia

    Juan M. Corchado

Authors
  1. Alfonso González-Briones
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  2. Pablo Chamoso
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  3. Sara Rodríguez
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  4. Angélica González-Arrieta
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  5. Juan M. Corchado
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Corresponding author

Correspondence to Alfonso González-Briones .

Editor information

Editors and Affiliations

  1. Universidad Nacional del Sur, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Simari

  2. University of Madeira, Funchal, Portugal

    Eduardo Fermé

  3. Universidad Nacional de Piura, Castilla-Piura, Peru

    Flabio Gutiérrez Segura

  4. Universidad Nacional de Trujillo, Trujillo, Peru

    José Antonio Rodríguez Melquiades

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González-Briones, A., Chamoso, P., Rodríguez, S., González-Arrieta, A., Corchado, J.M. (2018). Encouraging the Recycling Process of Urban Waste by Means of Game Theory Techniques Using a Multi-agent Architecture. In: Simari, G., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2018. IBERAMIA 2018. Lecture Notes in Computer Science(), vol 11238. Springer, Cham. https://doi.org/10.1007/978-3-030-03928-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-03928-8_10

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