A policy gradient reinforcement learning algorithm with fuzzy function approximation

Gu, Dongbing and Yang, Erfu; (2004) A policy gradient reinforcement learning algorithm with fuzzy function approximation. In: IEEE International Conference on Robotics and Biomimetics, 2004. ROBIO 2004. IEEE, CHN, pp. 936-940. ISBN 0780386148 (https://doi.org/10.1109/ROBIO.2004.1521910)

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Abstract

For complex systems, reinforcement learning has to be generalised from a discrete form to a continuous form due to large state or action spaces. In this paper, the generalisation of reinforcement learning to continuous state space is investigated by using a policy gradient approach. Fuzzy logic is used as a function approximation in the generalisation. To guarantee learning convergence, a policy approximator and a state action value approximator are employed for the reinforcement learning. Both of them are based on fuzzy logic. The convergence of the learning algorithm is justified.

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