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arXiv · 2008.01641

Exploring Variational Deep Q Networks

A. H. Bell-Thomas
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Abstract

This study provides both analysis and a refined, research-ready implementation of Tang and Kucukelbir's Variational Deep Q Network, a novel approach to maximising the efficiency of exploration in complex learning environments using Variational Bayesian Inference. Alongside reference implementations of both Traditional and Double Deep Q Networks, a small novel contribution is presented - the Double Variational Deep Q Network, which incorporates improvements to increase the stability and robustness of inference-based learning. Finally, an evaluation and discussion of the effectiveness of these approaches is discussed in the wider context of Bayesian Deep Learning.

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A. H. Bell-Thomas. 2020-08-04. Exploring Variational Deep Q Networks. https://arxiv.org/abs/2008.01641

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