Alejandro Weinstein
the EECS department of the Colorado School of Mines

Michael Wakin
the EECS department of the Colorado School of Mines

Abstract

This work describes the use some scientific Python tools to solve information gathering problems using Reinforcement Learning. In particular, we focus on the problem of designing an agent able to learn how to gather information in linked datasets. We use four different libraries—RL-Glue, Gensim, NetworkX, and scikit-learn—during different stages of our research. We show that, by using NumPy arrays as the default vector/matrix format, it is possible to integrate these libraries with minimal effort.

Keywords

reinforcement learning, latent semantic analysis, machine learning

DOI

10.25080/Majora-54c7f2c8-002

Bibtex entry

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Copyright © 2012 Alejandro Weinstein et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.