The Study of Recognizing Options Based on SMDP
Chan Su · 2005
The classical option algorithm provides a natural way of incorporating macro actions into Semi-Markov Decision Process (SMDP) framework. However it immediately raises the question of how to recognise appropriate options automatically. This paper presents a method based on the slope of frequenly curve to find sub-goals. Options can be automatically built based on sub-goals found in the previous step. This algorithm overcomes the shortcomings of previous methods such as low accuraly and artificial participation. We illustrated this algorithm with several grid-world navigation tasks. It is proved that the use of the options improve learning efficiency obviously.