Reinforcement Learning for Routing in Ad Hoc Networks
Petteri Nurmi
In: 5th Intl. Symposium on Modeling and Optimization, 16-20 Apr 2007, Limassol, Cypros.

Abstract

We show how routing in ad hoc networks can be modeled as a sequential decision making problem with incomplete information. More precisely, we show how to map routing into a reinforcement learning problem involving a partially observable Markov decision process, and present an algorithm for optimizing the performance of the nodes in this model. We also present simulation results with our model.

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