New book chapter

M. Bustos-López, N. Cruz-Ramírez,  A. Guerra-Hernández, L. N. Sánchez-Morales, and G. Alor-Hernández. New Perspectives on Enterprise Decision-Making Applying Artificial Intelligence, volume 966 of Studies in Computational Intelligence, chapter Emotion Detection from Text in Learning Environments: A Review, pages 483–508. Springer, Cham, Switzerland, 2021. | SpringerLink Abstract. Knowing student emotions allows teachers to efficiently adapt or…

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New article in JASSS

A. Platas-López, A. Guerra-Hernández, Francisco Grimaldo. On the Macroeconomic Effect of Extortion: An Agent-Based Approach. Journal of Artificial Societies and Social Simulation 24(1):3. January 2021. DOI: 10.18564/jasss.4496, ISSN 1460-7425 | JASSS Abstract. This work proposes an agent-based approach to study the effect of extortion on macroeconomic aggregates, despite the fact that there is little data on this criminal…

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New article in Applied Mathematical Modelling

A. Platas-López, E. Mezura-Montes, N. Cruz-Ramírez, A. Guerra-Hernández. Discriminative learning of bayesian network parameters by differential evolution. Applied Mathematical Modelling 93(2021): 244-256. December 2020. ISSN 0307-904X | ScienceDirect Abstract: This work proposes Differential Evolution (DE) to train parameters of Bayesian Networks (BN) for optimizing the Conditional Log-Likelihood (Discriminative Learning) instead of the log-likelihood (Generative Learning). Any…

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Research Lines (LGACs)

I introduced my research line on Agents, Learning and Simulation, for our new students in the Master in AI (MIA): 2020-lgacs-mia. (spanish).

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New article in Research in Computer Science

A. Platas-López, N. Cruz-Ramírez, E. Mezura-Montes, and A. Guerra-Hernández. Discriminative Parameter Learning of Bayesian Networks using differential evolution: A preliminary analysis. Research in Computing Science, 149(3):75–82, 2020. Abstract. This work proposes Differential Evolution (DE) to train parameters of Bayesian Networks (BN) for optimizing the Conditional Log-Likelihood (Discriminative Learning) instead of the log-likelihood (Generative Learning). Although…

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New article in Research in Computer Science

D. Martínez-Galicia, A. Guerra-Hernández, N. Cruz-Ramírez, X. Limón, and F. Grimaldo. Towards Windowing as a Sub-Sampling Method for Distributed Data Mining. Research in Computing Science, 149(3):57–64, 2020. Abstract. Windowing is a sub-sampling method that enables the induction of decision trees with large datasets. Using a small sample of the available training examples, the method can…

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New article in Mathematical and Computational Applications

D.Martínez Galicia, A. Guerra-Hernández, N. Cruz-Ramírez, X. Limón, F. Grimaldo. Windowing as a Sub-Sampling Method for Distributed Data Mining. Mathematical and Computational Applications,  25(3)1:39. June 2020. ISSN 2297-8747. Abstract: Windowing is a sub-sampling method, originally proposed to cope with large datasets when inducing decision trees with the ID3 and C4.5 algorithms. The method exhibits a strong negative…

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New Article in Studies in Computational Intelligence

A. Platas-López, A. Guerra-Hernández, N. Cruz-Ramírez, M. Quiroz-Castellanos, F. Grimaldo, M. Paolucci, and F. Cecconi. Intuitionistic and Type-2 Fuzzy Logic Ehancements in Neural and Op- timization Algorithms: Theory and Applications, volume 862 of Studies in Computational Intelligence, chapter Towards an Ageng-Based Model for Analysis of Macroeconomic Signals, pages 551–565. Springer, Cham, Switzerland, 2020.   Abstract….

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New paper accepted at CCIA 2019

Our paper “Micro-foundations of macroeconomic dynamics: the agent-based BAM model” has been accepted for presentation at CCIA 2019, to be held in Colonia de Sant Jordi. Congratulations to the co-authors: Alejandro Platas López, Federico Cecconi, Mario Paolucci, and Francisco Grimaldo. Abstract: This paper presents an open-source agent-based implementation of the BAM model, a micro-founded simulation…

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New paper at NEO 2019

Our paper “Analysis of Differential Evolution variants for parameter tuning of Decision Trees Inductive Algorithms” was accepted for its presentation at NEO 2019, to be held in Saltillo, México. The full program of the event will be available on August, 20th. Congratulations to the co-authors David Martínez Galicia y Efrén Mezura Montes. Extended abstract: This paper presents…

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