Dynamic Adjustment of the Motivation Degree in an Action Selection
  Mechanism
  This paper presents a model for dynamic adjustment of the motivation degree,
using a reinforcement learning approach, in an action selection mechanism
previously developed by the authors. The learning takes place in the
modification of a parameter of the model of combination of internal and
external stimuli. Experiments that show the claimed properties are presented,
using a VR simulation developed for such purposes. The importance of adaptation
by learning in action selection is also discussed.
