Safe Exploration Techniques for Reinforcement Learning - An Overview

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00223236" target="_blank" >RIV/68407700:21230/14:00223236 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Safe Exploration Techniques for Reinforcement Learning - An Overview
Original language description
We overview diferent approaches to safety in (semi)autonomous robotics. Particularly, we focus on how to achieve safe behavior of a robot if it is requested to perform exploration of unknown states. Presented methods are studied from the viewpoint of reinforcement learning, a partially-supervised machine learning method. Recently, it has shown to be one of the most suitable learning methods in robotics. However, to collect training data for this algorithm, the robot is required to freely explore the state space ? which can lead to possibly dangerous situations. The role of safe exploration is to provide a framework allowing exploration while preserving safety. The examined methods range from simple algorithms which utilize precise physical models to sophisticated methods based on previous experience or state prediction. Our overview also addresses the issues of how to define safety in the real-world applications. It is apparent that absolute safety is unachievable in the continuous and
Czech name
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Czech description
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Number of pages
10
Place of publication
Praha
Publisher/client name
Center for Machine Perception, K13133 FEE Czech Technical University
Version
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