A Systematic Review of Literature on Recommendation Systems and Machine Learning Applied to Multiagent Systems
Resumo
This study developed a systematic review of the literature (SRL), a formal study that is used to map a specific area of knowledge. The main question is defined that will guide the entire search during SRL including other formal steps. This SLR has been defined to synthesize and integrate the areas of multiagent systems, machine learning, and recommendation systems. At the end of the SRL, six studies with different characteristics were found that were adequate to the main question and that satisfy the selection criteria.Referências
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Brigui-Chtioui, I., Caillou, P., and Negre, E. (2017). Intelligent digital learning: agent-based recommender system. In Proceedings of the 9th International Conference on Machine Learning and Computing, pages 71–76.
Cazella, S. C., Nunes, M., and Reategui, E. (2010). A ciência da opinião: Estado da arte em sistemas de recomendação. André Ponce de Leon F. de Carvalho; Tomasz Kowaltowski..(Org.). Jornada de Atualização de Informática-JAI, pages 161–216.
Chornous, G. and Iarmolenko, I. (2017). Decision support system for predicting stock prices based on sentiments in social media. In Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing, pages 1–4.
Duggan, M., Duggan, J., Howley, E., and Barrett, E. (2017). A network aware approach for the scheduling of virtual machine migration during peak loads. Cluster Computing, 20(3):2083–2094.
El Naqa, I. and Murphy, M. J. (2015). What is machine learning? In machine learning in radiation oncology, pages 3–11. Springer.
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Harrington, P. (2012). Machine learning in action. Manning Publications Co.
Hübner, J. F., Bordini, R. H., and Vieira, R. (2004). Introdução ao desenvolvimento de sistemas multiagentes com jason. XII Escola de Informática da SBC, 2:51–89.
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Legien, G., Sniezynski, B., Wilk-Kołodziejczyk, D., Kluska-Nawarecka, S., Nawarecki, E., and Jaśkowiec, K. (2017). Agent-based decision support system for technology recommendation. Procedia Computer Science, 108:897–906.
Okoli, C. and Schabram, K. (2010). A guide to conducting a systematic literature review of information systems research. SSRN Electronic Journal.
Pinto, T. and Vale, Z. (2019). Albids: A decision support system for strategic bidding in electricity markets. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pages 2375–2377. International Foundation for Autonomous Agents and Multiagent Systems.
Shaft, D. and Cohen, R. (2013). A multiagent approach to ambulance allocation based on social welfare and local search. In 2013 12th International Conference on Machine Learning and Applications, volume 2, pages 384–389. IEEE.
Shalev-Shwartz, S. and Ben-David, S. (2014). Understanding machine learning: From theory to algorithms. Cambridge university press.
Silva, F., Pinto, T., and Vale, Z. (2019). Decision support system for opponents selection in electricity markets bilateral negotiations. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pages 2384–2386. International Foundation for Autonomous Agents and Multiagent Systems.
Singh, J. et al. (2010). Mendeley: A free research management tool for desktop and web. Journal of Pharmacology and Pharmacotherapeutics, 1(1):62.
Singh, M. P. (1994). Multiagent systems. Springer.
Team, J. D. et al. (2011). Jabref [software].
Weiss, G. (1999). Multiagent systems: a modern approach to distributed artificial intelligence. MIT press.
Zhang, Y. (2018). Key technologies of confrontational intelligent decision support for multi-agent systems. Automatic Control and Computer Sciences, 52(4):283–290.
Zhang, Y., Grignard, A., Lyons, K., Aubuchon, A., and Larson, K. (2018). Real-time machine learning prediction of an agent-based model for urban decision-making. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, pages 2171–2173. International Foundation for Autonomous Agents and Multiagent Systems.
Brigui-Chtioui, I., Caillou, P., and Negre, E. (2017). Intelligent digital learning: agent-based recommender system. In Proceedings of the 9th International Conference on Machine Learning and Computing, pages 71–76.
Cazella, S. C., Nunes, M., and Reategui, E. (2010). A ciência da opinião: Estado da arte em sistemas de recomendação. André Ponce de Leon F. de Carvalho; Tomasz Kowaltowski..(Org.). Jornada de Atualização de Informática-JAI, pages 161–216.
Chornous, G. and Iarmolenko, I. (2017). Decision support system for predicting stock prices based on sentiments in social media. In Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing, pages 1–4.
Duggan, M., Duggan, J., Howley, E., and Barrett, E. (2017). A network aware approach for the scheduling of virtual machine migration during peak loads. Cluster Computing, 20(3):2083–2094.
El Naqa, I. and Murphy, M. J. (2015). What is machine learning? In machine learning in radiation oncology, pages 3–11. Springer.
Galvão, T. F. and Pereira, M. G. (2014). Revisões sistemáticas da literatura: passos para sua elaboração. Epidemiologia e Serviços de Saúde, 23:183–184.
Harrington, P. (2012). Machine learning in action. Manning Publications Co.
Hübner, J. F., Bordini, R. H., and Vieira, R. (2004). Introdução ao desenvolvimento de sistemas multiagentes com jason. XII Escola de Informática da SBC, 2:51–89.
Kazík, O., Peková, K., Pilát, M., and Neruda, R. (2012). A novel meta learning system and its application to optimization of computing agents’ results. In 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, volume 2, pages 170–174. IEEE.
Kofod-Petersen, A. (2012). How to do a structured literature review in computer science. Ver. 0.1. October, 1.
Legien, G., Sniezynski, B., Wilk-Kołodziejczyk, D., Kluska-Nawarecka, S., Nawarecki, E., and Jaśkowiec, K. (2017). Agent-based decision support system for technology recommendation. Procedia Computer Science, 108:897–906.
Okoli, C. and Schabram, K. (2010). A guide to conducting a systematic literature review of information systems research. SSRN Electronic Journal.
Pinto, T. and Vale, Z. (2019). Albids: A decision support system for strategic bidding in electricity markets. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pages 2375–2377. International Foundation for Autonomous Agents and Multiagent Systems.
Shaft, D. and Cohen, R. (2013). A multiagent approach to ambulance allocation based on social welfare and local search. In 2013 12th International Conference on Machine Learning and Applications, volume 2, pages 384–389. IEEE.
Shalev-Shwartz, S. and Ben-David, S. (2014). Understanding machine learning: From theory to algorithms. Cambridge university press.
Silva, F., Pinto, T., and Vale, Z. (2019). Decision support system for opponents selection in electricity markets bilateral negotiations. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pages 2384–2386. International Foundation for Autonomous Agents and Multiagent Systems.
Singh, J. et al. (2010). Mendeley: A free research management tool for desktop and web. Journal of Pharmacology and Pharmacotherapeutics, 1(1):62.
Singh, M. P. (1994). Multiagent systems. Springer.
Team, J. D. et al. (2011). Jabref [software].
Weiss, G. (1999). Multiagent systems: a modern approach to distributed artificial intelligence. MIT press.
Zhang, Y. (2018). Key technologies of confrontational intelligent decision support for multi-agent systems. Automatic Control and Computer Sciences, 52(4):283–290.
Zhang, Y., Grignard, A., Lyons, K., Aubuchon, A., and Larson, K. (2018). Real-time machine learning prediction of an agent-based model for urban decision-making. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, pages 2171–2173. International Foundation for Autonomous Agents and Multiagent Systems.
Publicado
07/07/2020
Como Citar
RAMOS, Karine Pestana; AGUIAR, Marilton Sanchotene de.
A Systematic Review of Literature on Recommendation Systems and Machine Learning Applied to Multiagent Systems. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 14. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 128-139.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2020.33386.
