Gaussian processes for informative exploration in reinforcement learning

This paper presents the iGP-SARSA(λ) algorithm for temporal difference reinforcement learning (RL) with non-myopic information gain considerations. The proposed algorithm uses a Gaussian process (GP) model to approximate the state-action value function, Q, and incorporates the variance measure from...

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Bibliographische Detailangaben

Hauptverfasser:	Jen Jen Chung, Lawrance, Nicholas R. J., Sukkarieh, Salah
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Approximation algorithms Batteries Discharges (electric) Function approximation Tiles Training
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