Antonin Louis Leon Poche
Post-modelling Explainability for Deep Reinforcement Learning.
Rel. Giovanni Squillero. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021
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Abstract
Artificial Intelligence (AI) has developed tremendously in recent years, notably thanks to the advances in neural networks. However, the "black box" character of the latter has slowed down the diffusion of Deep Learning (DL) in the industry. Indeed, despite the growing efficiency of neural networks, they still do not have the confidence of industrials. This is why explainability is a rapidly expanding research sector. Delfox is working on Deep Reinforcement Learning (DRL) for important industrial actors working in particular with critical systems. Explainability applied to Reinforcement Learning (RL) is therefore a key issue for Delfox and thus it is the focus of this internship.
Explainability is still a young field of research and there is no industrial application of such a technology known to date
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