Cooperative Robots Used for the Learning Process in the Cooperative Work

  • Yoshua Haim Ovadiah
  • Gabriel Muñoz Samboni
  • John Páez Rodríguez
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 293)


This article describes the design and building process of a Learning Virtual Object that uses the Multiagent Systems theory to promote the thinking about advantages of cooperative work while solving problems. The software context is the environment care and for its execution users establish the cooperative conditions of three different robot groups responsible for collecting, classifying and storing three types of recyclable materials. Throughout the execution, the user evaluates if the established cooperative conditions are accurate to the correct task development. The software has been designed using Eclipse Kepler as IDE, Processing version 2.1 and the library AI for 2D Games and G4P to manage the robots states and the user interface respectively. The implementation results prove the software accuracy to learn how to cooperate in daily basis tasks through the cooperative robots programming, besides a conceptual change about cooperative concept that is evident in users, the team works the advantages and the distribute cognition principles for the cooperative tasks development.


Multiagent Systems Robotics Cooperative Work Virtual Learning Processes Environments 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Manuel, A.S.V., Carlos, G.C.: Trabajo en Equipo, el caso colombiano. Red de Revistas Científicas de América Latina, el Caribe, España y Portugal. Análisis Económico XX(43), 147–165 (2005)Google Scholar
  2. 2.
    Colombia, MEN. Estándares básicos de competencias ciudadanas, Colombia (2004)Google Scholar
  3. 3.
    Gregorio, C., Germán, C.: Investigación en administración en Ámerica Latina: Evolución y Resultados. Universidad Nacional. Colombia (2005)Google Scholar
  4. 4.
    Halverson, C.B., Aqeel, T.: Effective Multicultural Teams: Theory and Practice. Springer Science (2008)Google Scholar
  5. 5.
    West, M.A., Tjosvold, D., Smith, K.G.: International Handbook of Organizational Teamwork and Cooperative Working, England (2003)Google Scholar
  6. 6.
    Len, F.: The Perfect Swarm, The Science of complexity in everyday life. Basic Book, New York (2009)Google Scholar
  7. 7.
    Cao, Y.U., Fukunaga, A.S., Kahng, A.B.: Cooperative Mobile Robotics: Antecedents and Directions (1997)Google Scholar
  8. 8.
    Jacques, F.: Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Addison Wesley Longman, Harlow (1999)Google Scholar
  9. 9.
    Lewis, M.: Technics and Civilization. University of Chicago Press Edition (2010)Google Scholar
  10. 10.
    Brown, L.A., Walker, W.H.: Prologue: Archaeology, Animism and Non-Human Agents. Journal of Archaeological Method and Theory, 297–299 (2008)Google Scholar
  11. 11.
    Deval, J.: El animismo y el pensamiento infantil. Siglo XXI Editores, Madrid (1975)Google Scholar
  12. 12.
    Howard, G.: Frames of Mind, The Theory of Multiple Intelligences. Basic Books (1993)Google Scholar
  13. 13.
    Katherine, H.: How We Became Posthuman, Virtual Bodies in Cybernetics, Literature, and Informatics. The University of Chicago Press, Chicago er London (1999)Google Scholar
  14. 14.
    Michael, W., Dean, T., Ken, S.: International Handbook of Organizational Teamwork and Cooperative Working. John Wiley and Sons Ltd. (2003)Google Scholar
  15. 15.
    Wheeler, S.M.: Role Playing Games and Simulations for International Issues Courses. Journal of Political Science Education 2(3), 331–347 (2006)CrossRefGoogle Scholar
  16. 16.
    Margaret, H., Margaret, H.: Learning Science Through Computer Games and Simulations. Committee on Science Learning: Computer Games, Simulations, and Education; National Research Council (2011)Google Scholar
  17. 17.
    Nass, C., Moon, Y.: Machines and mindlessness: Social responses to computers. Journal of Social Issues 56(1), 81–103 (2000)CrossRefGoogle Scholar
  18. 18.
    Ron, S.: Cognition and Multi-Agent Interaction From Cognitive Modeling to Social Simulation. Cambridge University Press (2006)Google Scholar
  19. 19.
    Informe nacional sobre desarrollo humano 2013. Programa de las Naciones Unidas para el Desarrollo PNUD. 325 Páginas (2013)Google Scholar
  20. 20.
    Mitnik, R., Recabarren, M., Nussbaum, M., Soto, A.: Collaborative robotic instruction: A graph teaching experience (2009)Google Scholar
  21. 21.
    Barella, A., Valero, S., Carrascosa, C.: JGOMAS: New Approach to AI Teaching. IEEE Transactions on Education 52(2), 228–235 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yoshua Haim Ovadiah
    • 1
  • Gabriel Muñoz Samboni
    • 2
  • John Páez Rodríguez
    • 3
  1. 1.Lic. PhysicUniversidad Distrital Francisco José de CaldasBogotáColombia
  2. 2.Systems EngineerUniversidad del CaucaBogotáColombia
  3. 3.Faculty of Science and EducationUniversidad Distrital Francisco José de CaldasBogotáColombia

Personalised recommendations