Dynamic Adjustment of the Motivation Degree in an Action Selection Mechanism
Carlos Gershenson, Pedro Pablo Gonzalez
Abstract
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.
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