Reinforcement Learning for Adaptive Routing

Details Reinforcement Learning for Adaptive Routing Reinforcement Learning for Adaptive Routing

2007-03-28

arxiv.org/abs/cs/0703138v1

In Proceedings of the Intnl Joint Conf on Neural Networks (IJCNN), 2002

Computer Science

Learning

Scientific paper

Reinforcement learning means learning a policy--a mapping of observations into actions--based on feedback from the environment. The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment. We present an application of gradient ascent algorithm for reinforcement learning to a complex domain of packet routing in network communication and compare the performance of this algorithm to other routing methods on a benchmark problem.

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