Living in a partially structured environment: How to bypass the limitations of classical reinforcement techniques

Authors: Gaussier P.; Revel A.; Joulain C.; Zrehen S.

Source: Robotics and Autonomous Systems, Volume 20, Number 2, June 1997 , pp. 225-250(26)

Publisher: Elsevier

Keywords: Neural networks; Unsupervised learning; Topological maps; Reinforcement; Autonomous robot; All-or-none learning

Language: English

Document Type: Research article

DOI: http://dx.doi.org/10.1016/S0921-8890(97)80708-7

Affiliations: 1: ETIS-ENSEA/Cergy University, 6 Av. du Ponceau, 95014 Cergy Pontoise Cedex, France

Publication date: 1997-06-01

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• In this Subject: Materials & Manufacturing ,  Mechanical Engineering
• By this author: Gaussier P. ;  Revel A. ;  Joulain C. ;  Zrehen S.

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