Algorithm Analysis in Multi-agent Systems
Abstract This paper presents a multi-agent system that looks for the most optimum algorithm of its type. For that purpose it will use several agents which will be in charge of testing the algorithms and comparing the outcome to see which is the most efficient. Thanks to this procedure the most optimum procedure can be obtained.
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Blanco-Fernandez, Y. et al., 2004. AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning. s.l., s.n., pp. 415-421. https://doi.org/10.1007/978-3-540-30480-7_43
Bedi, P., Agarwal, S. K., Jindal, V. & Richa, 2014. MARST: Multi-Agent Recommender System for e-Tourism Using Reputation Based Collaborative Filtering. New York, NY, USA, Springer-Verlag New York, Inc., pp. 189-201 https://doi.org/10.1007/978-3-319-05693-7_12
Blanco-Fernández Yolanda, Pazos-Arias José J., Gil-Solla Alberto, Ramos-Cabrer Manuel, Barragáns-Martínez Belén, López-Nores Martín, García-Duque Jorge, Fernández-Vilas Ana, and P. Díaz-Redondo Rebeca, 2004. AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning. In: Zhou X., Su S., Papazoglou M.P., Orlowska M.E., Jeffery K. (eds) Web Information Systems - WISE 2004. WISE 2004. Lecture Notes in Computer Science, vol 3306. Springer, Berlin, Heidelberg https://doi.org/10.1007/978-3-540-30480-7_43
Christian Paulo Villavicencio, Silvia Schiaffino, J. Andrés Díaz-Pace, and Ariel Monteserin, 2016. A Group Recommendation System for Movies based on MAS. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, Salamanca, v. 5, n. 3, p. 1-12, nov. 2016. ISSN 2255-2863. https://doi.org/10.14201/ADCAIJ201653112
Consensus-based Approach for Keyword Extraction from Urban Events Collections Ana Alvesa, b, Bernardete Ribeiroa a CISUC, Department of Informatics Engineering, University of Coimbra, Portugal, 2015.
De la Prieta Pintado Fernando, Rodríguez González Sara, Corchado Rodríguez Juan M., and Bajo Pérez Javier, 2015. Infrastructure to Simulate Intelligent Agents in Cloud Environments, Journal of Intelligent and Fuzzy Systems, IOS Press. https://doi.org/10.3233/IFS-141219
Marivate, V. N., Ssali, G., & Marwala, T., 2008. An Intelligent Multi-Agent Recommender System for Human Capacity Building. s.l., IEEE, pp. 909-915. https://doi.org/10.1109/MELCON.2008.4618553
Tan, M., 1991. Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents, GTE Laboratories Incorporated,
Wooldridge, M., and Jennings, N.R., 1995. Agent Theories, Architectures, and Languages: A Survey, In: Intelligent Agents, Springer. https://doi.org/10.1007/3-540-58855-8_1
Wu, D. J., 2001. Software agents for knowledge management: coordination in multi-agent supply chains and auctions, University of Pennsylvania 2001 https://doi.org/10.1016/S0957-4174(00)00048-8
Zambonelli F., Jennings N.R., and Wooldridge M., 2003. Developing multiagent systems: The gaia methodology, ACM Transactions on Software Engineering and Methodology. https://doi.org/10.1145/958961.958963
Bedi, P., Agarwal, S. K., Jindal, V. & Richa, 2014. MARST: Multi-Agent Recommender System for e-Tourism Using Reputation Based Collaborative Filtering. New York, NY, USA, Springer-Verlag New York, Inc., pp. 189-201 https://doi.org/10.1007/978-3-319-05693-7_12
Blanco-Fernández Yolanda, Pazos-Arias José J., Gil-Solla Alberto, Ramos-Cabrer Manuel, Barragáns-Martínez Belén, López-Nores Martín, García-Duque Jorge, Fernández-Vilas Ana, and P. Díaz-Redondo Rebeca, 2004. AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning. In: Zhou X., Su S., Papazoglou M.P., Orlowska M.E., Jeffery K. (eds) Web Information Systems - WISE 2004. WISE 2004. Lecture Notes in Computer Science, vol 3306. Springer, Berlin, Heidelberg https://doi.org/10.1007/978-3-540-30480-7_43
Christian Paulo Villavicencio, Silvia Schiaffino, J. Andrés Díaz-Pace, and Ariel Monteserin, 2016. A Group Recommendation System for Movies based on MAS. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, Salamanca, v. 5, n. 3, p. 1-12, nov. 2016. ISSN 2255-2863. https://doi.org/10.14201/ADCAIJ201653112
Consensus-based Approach for Keyword Extraction from Urban Events Collections Ana Alvesa, b, Bernardete Ribeiroa a CISUC, Department of Informatics Engineering, University of Coimbra, Portugal, 2015.
De la Prieta Pintado Fernando, Rodríguez González Sara, Corchado Rodríguez Juan M., and Bajo Pérez Javier, 2015. Infrastructure to Simulate Intelligent Agents in Cloud Environments, Journal of Intelligent and Fuzzy Systems, IOS Press. https://doi.org/10.3233/IFS-141219
Marivate, V. N., Ssali, G., & Marwala, T., 2008. An Intelligent Multi-Agent Recommender System for Human Capacity Building. s.l., IEEE, pp. 909-915. https://doi.org/10.1109/MELCON.2008.4618553
Tan, M., 1991. Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents, GTE Laboratories Incorporated,
Wooldridge, M., and Jennings, N.R., 1995. Agent Theories, Architectures, and Languages: A Survey, In: Intelligent Agents, Springer. https://doi.org/10.1007/3-540-58855-8_1
Wu, D. J., 2001. Software agents for knowledge management: coordination in multi-agent supply chains and auctions, University of Pennsylvania 2001 https://doi.org/10.1016/S0957-4174(00)00048-8
Zambonelli F., Jennings N.R., and Wooldridge M., 2003. Developing multiagent systems: The gaia methodology, ACM Transactions on Software Engineering and Methodology. https://doi.org/10.1145/958961.958963
Pacheco, L., Sánchez, N., Tur, A., & Tellez De Meneses, D. (2019). Algorithm Analysis in Multi-agent Systems. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8(1), 13–18. https://doi.org/10.14201/ADCAIJ2019811318
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