Learning to Coordinate Multi-robot Competitive Systems by Stimuli Adaptation
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.
KeywordsReinforcement Learning Adaptive System Linear Speed Basic Behavior Reinforcement Learning Algorithm
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