Open access peer-reviewed chapter

Complex-Valued Reinforcement Learning: a Context-Based Approach for POMDPs

By Takeshi Shibuya and Tomoki Hamagami

Submitted: April 26th 2010Reviewed: August 19th 2010Published: January 14th 2011

DOI: 10.5772/13295

Downloaded: 1300

© 2011 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike-3.0 License, which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited and derivative works building on this content are distributed under the same license.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Takeshi Shibuya and Tomoki Hamagami (January 14th 2011). Complex-Valued Reinforcement Learning: a Context-Based Approach for POMDPs, Advances in Reinforcement Learning, Abdelhamid Mellouk, IntechOpen, DOI: 10.5772/13295. Available from:

chapter statistics

1300total chapter downloads

1Crossref citations

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Adaptive PID Control of a Nonlinear Servomechanism Using Recurrent Neural Networks

By Reza Jafari and Rached Dhaouadi

Related Book

First chapter

Neural Machine Learning Approaches: Q-Learning and Complexity Estimation Based Information Processing System

By Abdennasser Chebira, Abdelhamid Mellouk, Kurosh Madani and Said Hoceini

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

More About Us