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arXiv · 1806.04552

Combining Model-Free Q-Ensembles and Model-Based Approaches for Informed Exploration

Sreecharan Sankaranarayanan·Raghuram Mandyam Annasamy·Katia Sycara·Carolyn Penstein Rosé
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Abstract

Q-Ensembles are a model-free approach where input images are fed into different Q-networks and exploration is driven by the assumption that uncertainty is proportional to the variance of the output Q-values obtained. They have been shown to perform relatively well compared to other exploration strategies. Further, model-based approaches, such as encoder-decoder models have been used successfully for next frame prediction given previous frames. This paper proposes to integrate the model-free Q-ensembles and model-based approaches with the hope of compounding the benefits of both and achieving superior exploration as a result. Results show that a model-based trajectory memory approach when combined with Q-ensembles produces superior performance when compared to only using Q-ensembles.

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BibTeXRIS

Sreecharan Sankaranarayanan, Raghuram Mandyam Annasamy, Katia Sycara, Carolyn Penstein Rosé. 2018-06-12. Combining Model-Free Q-Ensembles and Model-Based Approaches for Informed Exploration. https://arxiv.org/abs/1806.04552

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