Learning to Coordinate Multi-robot Competitive Systems by Stimuli Adaptation

  • José Antonio Martín H.
  • Javier de Lope
  • Darío Maravall
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5602)


The area of competitive robotic systems usually yields to highly complicated strategies that must be achieved by complex learning architectures since analytic solutions seems to be unpractical or unfeasible at all. In this work we design an experiment in order to study and validate a model in the task of learning to coordinate a robot team to achieve complex goals by means of a simulation of a multi-robot competitive task that imitates a complex prey/predator system composed by three robots: predator, defender and prey. By means of such simulation we validate a general model about the complex phenomena of adaptation, anticipation and rationality.


Reinforcement Learning Adaptive System Linear Speed Basic Behavior Reinforcement Learning Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • José Antonio Martín H.
    • 1
  • Javier de Lope
    • 2
  • Darío Maravall
    • 2
  1. 1.Dep. Sistemas Informáticos y ComputaciónUniversidad Complutense de MadridSpain
  2. 2.Perception for Computers and RobotsUniversidad Politécnica de MadridSpain

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