Jose Manuel Galan

Personal Details

First Name:	Jose
Middle Name:	Manuel
Last Name:	Galan
Suffix:
RePEc Short-ID:	pga177
	[This author has chosen not to make the email address public]
	https://sites.google.com/site/josemagalan/
	José M. Galán Ordax Universidad de Burgos Escuela Politécnica Superior Ed. La Milanera. C/ Villadiego s/n Burgos 09001
Terminal Degree:	2007 (from RePEc Genealogy)

Affiliation

(50%) Grupo de Ingeniería de los Sistemas Sociales (INSISOC)
Universidad de Valladolid

Valladolid, Spain
http://www.insisoc.org/
RePEc:edi:givldes (more details at EDIRC)

(50%) Área de Organización de Empresas
Departamento de Ingenería Civil
Universidad de Burgos

Burgos, Spain
http://www2.ubu.es/ingciv/orgemp/
RePEc:edi:aoubues (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

1. Andreas Angourakis & José Ignacio Santos & José Manuel Galán & Andrea L. Balbo, 2015. "Food for all: An agent-based model to explore the emergence and implications of cooperation for food storage," Environmental Archaeology, Taylor & Francis Journals, vol. 20(4), pages 349-363, November.

   Cited by:

   1. Snellman, Jan E. & Barrio, Rafael A. & Kaski, Kimmo K., 2021. "Social structure formation in a network of agents playing a hybrid of ultimatum and dictator games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).

2. Samer Hassan & Javier Arroyo & José Manuel Galán & Luis Antunes & Juan Pavón, 2013. "Asking the Oracle: Introducing Forecasting Principles into Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(3), pages 1-13.

   Cited by:

   1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
   2. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2014. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," FinMaP-Working Papers 26, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
      • Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.

3. Rubén Fuentes-Fernández & Samer Hassan & Juan Pavón & José M. Galán & Adolfo López-Paredes, 2012. "Metamodels for role-driven agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 91-112, March.

   Cited by:

   1. David Passenier & Colin Mols & Jan Bím & Alexei Sharpanskykh, 2016. "Modeling safety culture as a socially emergent phenomenon: a case study in aircraft maintenance," Computational and Mathematical Organization Theory, Springer, vol. 22(4), pages 487-520, December.
   2. Bing Bai & Byungjoon Yoo & Xiuquan Deng & Iljoo Kim & Dehua Gao, 2016. "Linking routines to the evolution of IT capability on agent-based modeling and simulation: a dynamic perspective," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 184-211, June.
   3. Matthias Meyer & Klaus G. Troitzsch, 2012. "Epistemological perspectives on simulation: overview and introduction," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 1-4, March.

4. José M Galán & Maciej M Łatek & Seyed M Mussavi Rizi, 2011. "Axelrod's Metanorm Games on Networks," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-11, May.

   Cited by:

   1. Duan-Bing Chen & Hui Gao & Linyuan Lü & Tao Zhou, 2013. "Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-10, October.

5. David J Poza & José I Santos & José M Galán & Adolfo López-Paredes, 2011. "Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-11, March.

   Cited by:

   1. Su, Lichen & Yang, Zhengzhi & Zhou, Bowen & Zhang, Naitian & Li, Yumeng, 2023. "Effects of interdependent network reciprocity on the evolution of public cooperation," Applied Mathematics and Computation, Elsevier, vol. 454(C).

6. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.

   Cited by:

   1. Nieddu, Marcello & Bertani, Filippo & Ponta, Linda, 2021. "Sustainability transition and digital trasformation: an agent-based perspective," MPRA Paper 106943, University Library of Munich, Germany.
   2. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
   3. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
      • Paola Tubaro, 2011. "Computational economics," Post-Print hal-01372973, HAL.
   4. J. Gareth Polhill, 2015. "Extracting OWL Ontologies from Agent-Based Models: A Netlogo Extension," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-15.
   5. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
   6. Nancy Quinceno Cárdenas, 2014. "Modelación basada en agentes en el sistema pensional colombiano. Una aproximación desde el mercado laboral y la dinámica poblacional," Revista CIFE, Universidad Santo Tomás, September.
   7. Sung-youn Kim, 2011. "A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(2), pages 1-3.
   8. Bernardo Alves Furtado, 2018. "Modeling tax distribution in metropolitan regions with PolicySpace," Papers 1901.02391, arXiv.org.
   9. José M Galán & Maciej M Łatek & Seyed M Mussavi Rizi, 2011. "Axelrod's Metanorm Games on Networks," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-11, May.
   10. Barroso, Ricardo Vieira & Lima, Joaquim Ignacio Alves Vasconcellos & Lucchetti, Alexandre Henrique & Cajueiro, Daniel Oliveira, 2016. "Interbank network and regulation policies: an analysis through agent-based simulations with adaptive learning," MPRA Paper 73308, University Library of Munich, Germany.
   11. Kolkman, Daan, 2020. "The usefulness of algorithmic models in policy making," SocArXiv hpma8, Center for Open Science.
   12. Jacopo Baggio & Elissaios Papyrakis, 2014. "Agent-Based Simulations of Subjective Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(2), pages 623-635, January.
   13. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
   14. Sara Lumbreras & Sonja Wogrin & Guillermo Navarro & Ilaria Bertazzi & Maria Pereda, 2019. "A Decentralized Solution for Transmission Expansion Planning: Getting Inspiration from Nature," Energies, MDPI, vol. 12(23), pages 1-17, November.
   15. Rubén Fuentes-Fernández & Samer Hassan & Juan Pavón & José M. Galán & Adolfo López-Paredes, 2012. "Metamodels for role-driven agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 91-112, March.
   16. Bernardo Alves Furtado & Gustavo Onofre Andre~ao, 2022. "Machine Learning Simulates Agent-Based Model Towards Policy," Papers 2203.02576, arXiv.org, revised Nov 2022.
   17. Marcello Nieddu & Filippo Bertani & Linda Ponta, 2022. "The sustainability transition and the digital transformation: two challenges for agent-based macroeconomic models," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 193-226, April.
   18. Georg Holtz & Christian Schnülle & Malcolm Yadack & Jonas Friege & Thorben Jensen & Pablo Thier & Peter Viebahn & Émile J. L. Chappin, 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies," Energies, MDPI, vol. 13(22), pages 1-26, November.

7. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.

   Cited by:

   1. Catalano, Michele & Di Guilmi, Corrado, 2019. "Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 117-144.
      • Michele Catalano & Corrado Di Guilmi, 2016. "Uncertainty, rationality and complexity in a multi sectoral dynamic model: the Dynamic Stochastic Generalized Aggregation approach," CAMA Working Papers 2016-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   2. Wyburn, John & Hayward, John, 2019. "An application of an analogue of the partition function to the evolution of diglossia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 447-463.
   3. Andrew W. Bausch, 2014. "Evolving intergroup cooperation," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 369-393, December.
   4. Pfau, Jens & Kirley, Michael & Kashima, Yoshihisa, 2013. "The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod’s model of cultural dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 381-391.
   5. Corrado Di Guilmi & Laura Carvalho, 2016. "The Dynamics Of Leverage In A Demand-Driven Model With Heterogeneous Firms," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 141, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
      • Di Guilmi, Corrado & Carvalho, Laura, 2017. "The dynamics of leverage in a demand-driven model with heterogeneous firms," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 70-90.
   6. Sven Banischa & Ricardo Lima & Tanya Araújo, 2012. "Agent based models and opinion dynamics as markov chains," Working Papers Department of Economics 2012/10, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
   7. Declan Mungovan & Enda Howley & Jim Duggan, 2011. "The influence of random interactions and decision heuristics on norm evolution in social networks," Computational and Mathematical Organization Theory, Springer, vol. 17(2), pages 152-178, May.
   8. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
   9. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
      • Jakob Grazzini & Matteo Richiardi, 2014. "Estimation of Ergodic Agent-Based Models by Simulated Minimum Distance," Economics Papers 2014-W07, Economics Group, Nuffield College, University of Oxford.
   10. José M Galán & Maciej M Łatek & Seyed M Mussavi Rizi, 2011. "Axelrod's Metanorm Games on Networks," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-11, May.
   11. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
       • Grazzini, Jakob & Richiardi, Matteo, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201335, University of Turin.
   12. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046.
   13. Akihisa Okada & Daisuke Inoue & Shihori Koyama & Tadayoshi Matsumori & Hiroaki Yoshida, 2022. "Dynamical cooperation model for mitigating the segregation phase in Schelling’s model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(10), pages 1-10, October.
   14. Edoardo Gaffeo & Mauro Gallegati & Umberto Gostoli, 2015. "An agent-based “proof of principle” for Walrasian macroeconomic theory," Computational and Mathematical Organization Theory, Springer, vol. 21(2), pages 150-183, June.
       • Edoardo Gaffeo & Mauro Gallegati & Umberto Gostoli, 2012. "An agent-based "proof of principle" for Walrasian macroeconomic theory," CEEL Working Papers 1202, Cognitive and Experimental Economics Laboratory, Department of Economics, University of Trento, Italia.
   15. Severin Reissl, 2022. "Fiscal multipliers, expectations and learning in a macroeconomic agent‐based model," Economic Inquiry, Western Economic Association International, vol. 60(4), pages 1704-1729, October.

8. José Manuel Galán & Luis R. Izquierdo, 2005. "Appearances Can Be Deceiving: Lessons Learned Re-Implementing Axelrod's 'Evolutionary Approach to Norms'," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(3), pages 1-2.

   Cited by:

   1. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
   2. Hitoshi Yamamoto & Takahisa Suzuki, 2018. "Effects of beliefs about sanctions on promoting cooperation in a public goods game," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-6, December.
   3. Claudio J. Tessone & Angel Sanchez & Frank Schweitzer, "undated". "Diversity-induced resonance in the response to social norms," Working Papers ETH-RC-12-017, ETH Zurich, Chair of Systems Design.
   4. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
   5. Dirk Helbing & Anders Johansson, 2010. "Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-15, October.
   6. J. Gareth Polhill & Dawn C. Parker & Daniel Brown & Volker Grimm, 2008. "Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-3.
   7. José M Galán & Maciej M Łatek & Seyed M Mussavi Rizi, 2011. "Axelrod's Metanorm Games on Networks," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-11, May.
   8. Luis R. Izquierdo & J. Gareth Polhill, 2006. "Is Your Model Susceptible to Floating-Point Errors?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(4), pages 1-4.
   9. Bruce Edmonds, 2010. "Bootstrapping Knowledge About Social Phenomena Using Simulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-8.
   10. Uri Wilensky & William Rand, 2007. "Making Models Match: Replicating an Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-2.
   11. J. Gareth Polhill & Bruce Edmonds, 2007. "Open Access for Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-10.
   12. J. Gareth Polhill & Edoardo Pignotti & Nicholas M. Gotts & Pete Edwards & Alun Preece, 2007. "A Semantic Grid Service for Experimentation with an Agent-Based Model of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-2.
   13. Fujio Toriumi & Hitoshi Yamamoto & Isamu Okada, 2020. "A belief in rewards accelerates cooperation on consumer-generated media," Journal of Computational Social Science, Springer, vol. 3(1), pages 19-31, April.
   14. Yamamoto, Hitoshi & Okada, Isamu, 2016. "How to keep punishment to maintain cooperation: Introducing social vaccine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 526-536.
   15. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
   16. Peter Revay & Claudio Cioffi-Revilla, 2018. "Survey of evolutionary computation methods in social agent-based modeling studies," Journal of Computational Social Science, Springer, vol. 1(1), pages 115-146, January.
   17. Martin Neumann, 2008. "Homo Socionicus: a Case Study of Simulation Models of Norms," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(4), pages 1-6.
   18. Segismundo S. Izquierdo & Luis R. Izquierdo & Nicholas M. Gotts, 2008. "Reinforcement Learning Dynamics in Social Dilemmas," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-1.

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