Abstract
The increase in population is increasing the growth of the number of residues. A large amount of this waste can be recycled so that it does not remain in uncontrolled landfills, pollute air, land or water. Although many campaigns and policies of recycling have been developed all-way there is not a total awareness about this problem and a large number of waste does not end up in the right place to be recycled. It is necessary to increase the amount of recycled waste and for this citizen participation is key. It is vital to involve the population in a more active way to recycle through some kind of social benefit. For this reason, GarbMAS proposes a system that generates a motivation for citizen participation by reducing the garbage tax applied by its local government. Thus, the increase in the amount of waste collected to be recycled is expected. GarbMAS employs a multi-agent system that simulates data collection and efficient waste management in cities through gamification techniques to produce the change motivation of citizens and therefore increase participation and recycled quantity. The case study in which the simulation was carried out showed an increase in citizen participation by 34.2% and an increase of 29.4% in the amount of waste collected.
J. A. García Coria—IEEE.
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Acknowledgements
This research has been partially supported by the European Regional Development Fund (FEDER) within the framework of the Interreg program V-A Spain-Portugal 2014-2020 (PocTep) under the IOTEC project grant 0123_IOTEC_3_E and by FEDER funds under the projects TIN2016-75850-R. The research of Alfonso González-Briones has been co-financed by the European Social Fund (Operational Programme 2014-2020 for Castilla y León, EDU/310/2015 BOCYL).
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González-Briones, A. et al. (2019). 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) Distributed Computing and Artificial Intelligence, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-319-94649-8_40
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