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Value-gradient learning

Fairbank, Michael and Alonso, Eduardo (2012) Value-gradient learning. In: The 2012 International Joint Conference on Neural Networks (IJCNN), 2012-06-10 - 2012-06-15, Brisbane, QLD, Australia.

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Abstract

We describe an Adaptive Dynamic Programming algorithm VGL (λ) for learning a critic function over a large continuous state space. The algorithm, which requires a learned model of the environment, extends Dual Heuristic Dynamic Programming to include a bootstrapping parameter analogous to that used in the reinforcement learning algorithm TD(λ). We provide on-line and batch mode implementations of the algorithm, and summarise the theoretical relationships and motivations of using this method over its precursor algorithms Dual Heuristic Dynamic Programming and TD (λ). Experiments for control problems using a neural network and greedy policy are provided.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: The 2012 International Joint Conference on Neural Networks (IJCNN)
Uncontrolled Keywords: Value-Gradient Learning, Dual Heuristic Dynamic Programming, DHP, Adaptive Dynamic Programming
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 14 Apr 2021 13:38
Last Modified: 14 Apr 2021 14:15
URI: http://repository.essex.ac.uk/id/eprint/21299

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