Iterative Oblique Decision Trees Deliver Explainable RL Models

The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque deep reinforcement learning (DRL) agents. We in...

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Ngā kaituhi matua:	Raphael C. Engelhardt, Marc Oedingen, Moritz Lange, Laurenz Wiskott, Wolfgang Konen
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2023-05-01
Rangatū:	Algorithms
Ngā marau:	reinforcement learning decision tree explainable AI rule learning
Urunga tuihono:	https://www.mdpi.com/1999-4893/16/6/282
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

Iterative Oblique Decision Trees Deliver Explainable RL Models

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