@inproceedings{6062220e4e344571b668b2539d76c70f,
title = "Simultaneous learning of perceptions and actions in autonomous robots",
abstract = "This paper presents a new learning approach for autonomous robots. Our system will learn simultaneously the perception - the set of states relevant to the task - and the action to execute on each state for the task-robot- environment triad. The objective is to solve two problems that are found when learning new tasks with robots: interpretability of the learning process and number of parameters; and the complex design of the state space. The former was solved using a new reinforcement learning algorithm that tries to maximize the time before failure in order to obtain a control policy suitable to the desired behavior. The state representation will be created dynamically, starting with an empty state space and adding new states as the robot finds them, this makes unnecessary the creation of a predefined state representation, which is a tedious task.",
keywords = "Autonomous robots, Fuzzy art, Reinforcement learning, State representation",
author = "Pablo Quint{\'i}a and Roberto Iglesias and Miguel Rodr{\'i}guez and Regueiro, {Carlos V.}",
year = "2010",
language = "English",
isbn = "9789898425010",
series = "ICINCO 2010 - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics",
pages = "395--398",
booktitle = "ICINCO 2010 - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics",
note = "7th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2010 ; Conference date: 15-06-2010 Through 18-06-2010",
}