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Finished first draft of outline
Signed-off-by: Jim Martens <github@2martens.de>
This commit is contained in:
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% Encoding: UTF-8
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@Article{French1999,
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Title = {Catastrophic forgetting in connectionist networks},
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Author = {French, Robert M},
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Journaltitle = {Trends in cognitive sciences},
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Year = {1999},
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Number = {4},
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Pages = {128--135},
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Volume = {3},
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Owner = {jim},
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Timestamp = {2018.04.20}
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}
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@Article{Kirkpatrick2017,
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Title = {Overcoming catastrophic forgetting in neural networks},
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Author = {Kirkpatrick, James and Pascanu, Razvan and Rabinowitz, Neil and Veness, Joel and Desjardins, Guillaume and Rusu, Andrei A and Milan, Kieran and Quan, John and Ramalho, Tiago and Grabska-Barwinska, Agnieszka and others},
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Journaltitle = {Proceedings of the National Academy of Sciences},
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Year = {2017},
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Number = {13},
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Pages = {3521--3526},
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Volume = {114},
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Owner = {jim},
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Timestamp = {2018.04.20}
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}
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@Book{Leunen:Scholars:92,
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@Book{Leunen:Scholars:92,
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author = {M.-C. van Leunen},
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Title = {A Handbook for Scholars},
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title = {A Handbook for Scholars},
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Author = {M.-C. van Leunen},
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publisher = {Oxford University Press},
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Year = {1992},
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year = 1992
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Publisher = {Oxford University Press}
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}
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@Inproceedings{Shmelkov2017,
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Title = {Incremental Learning of Object Detectors without Catastrophic Forgetting},
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Author = {Shmelkov, Konstantin and Schmid, Cordelia and Alahari, Karteek},
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Booktitle = {ICCV},
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Date = {2017-10-22/2017-10-29},
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Year = {2017},
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Publisher = {IEEE},
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Journaltitle = {arXiv preprint arXiv:1708.06977},
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Owner = {jim},
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Timestamp = {2018.04.20}
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}
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}
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@Misc{Taylor:SIGuide:95,
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@Misc{Taylor:SIGuide:95,
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author = {B. N. Taylor},
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Title = {Guide for the Use of the International System of Units (SI)},
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title = {Guide for the Use of the International System of Units (SI)},
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Author = {B. N. Taylor},
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howpublished = {NIST Special Publication 811},
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Year = {1995},
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year = 1995,
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HowPublished = {NIST Special Publication 811},
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note = {\url{http://physics.nist.gov/Document/sp811.pdf}}
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Note = {\url{http://physics.nist.gov/Document/sp811.pdf}}
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}
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}
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@Inbook{Toutounji2016,
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Title = {Autonomous Learning Needs a Second Environmental Feedback Loop},
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Author = {Toutounji, Hazem and Pasemann, Frank},
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Booktitle = {Computational Intelligence},
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Year = {2016},
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Pages = {455--472},
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Publisher = {Springer},
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Owner = {jim},
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Timestamp = {2018.04.20}
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}
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@Article{Velez2017,
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Title = {Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks},
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Author = {Velez, Roby and Clune, Jeff},
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Journaltitle = {PloS one},
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Year = {2017},
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Editor = {Irene Sendiña-Nadal},
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Number = {11},
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Pages = {e0187736},
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Volume = {12},
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Owner = {jim},
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Timestamp = {2018.04.20}
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}
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@ -21,7 +21,7 @@
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% \selectlanguage{german}
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% \selectlanguage{german}
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% If the thesis is written in English:
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% If the thesis is written in English:
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\usepackage[english]{babel}
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\usepackage[spanish,english]{babel}
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\selectlanguage{english}
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\selectlanguage{english}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\usepackage{fancybox} % Gleichungen einrahmen
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\usepackage{fancybox} % Gleichungen einrahmen
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%\usepackage{fancyhdr} % Packet for nicer headers
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%\usepackage{fancyhdr} % Packet for nicer headers
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\usepackage[automark]{scrlayer-scrpage}
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\usepackage[automark]{scrlayer-scrpage}
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\usepackage[hidelinks]{hyperref}\urlstyle{rm}
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%\usepackage{fancyheadings} % Nicer numbering of headlines
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%\usepackage{fancyheadings} % Nicer numbering of headlines
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%\usepackage[outer=3.35cm]{geometry} % Type area (size, margins...) !!!Release version
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%\usepackage[outer=3.35cm]{geometry} % Type area (size, margins...) !!!Release version
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\usepackage[
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\usepackage[
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backend=biber,
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backend=biber,
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bibstyle=ieee,
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bibstyle=ieee,
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citestyle=ieee
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citestyle=ieee,
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minnames=1,
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maxnames=2
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]{biblatex}
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]{biblatex}
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\addbibresource{bib.bib}
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\addbibresource{bib.bib}
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@ -201,15 +204,67 @@ citestyle=ieee
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\section{Introduction}
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\section{Introduction}
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\label{sec:introduction}
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\label{sec:introduction}
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Your text here...
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Autonomous robots need to adapt to new situations. They have a need to learn
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for an entire life. In order to do this they need a second environmental feedback
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loop that tells them when to learn.\cite{Toutounji2016}
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\cite{Leunen:Scholars:92}
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The learning poses another problem as well. The previously learned weights
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\cite{Taylor:SIGuide:95}
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are usually largely forgotten, which is known as catastrophic forgetting.\cite{French1999}
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Since catastrophic forgetting is a key problem for autonomous learning, it is
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crucial to overcome it. In this paper I will present some approaches for
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learning in an autonomous setup to analyse which of them if any can overcome
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catastrophic forgetting. Attempts to overcome that were made by
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Kirkpatrick\cite{Kirkpatrick2017}, Velez\cite{Velez2017} and Shmelkov\cite{Shmelkov2017}.
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\section{Neuromodulation}
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\label{sec:neuromodulation}
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Neuromodulation is a way to implement the second environmental feedback loop.
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A Modulated Neural Network (MNN) contains neuromodulator cells (NMC), which are
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attached to carrier neurons with a modulatory subnetwork (MSN).
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Neuromodulation can also be done based upon Diffusion.
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\section{Plasticity}
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\label{sec:plasticity}
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Plasticity can be realized by various approaches. Here three approaches are
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presented, Modulated Random Search, Modulated Gaussian Walk and Diffusion based
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neuromodulation.
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\subsection{Modulated Random Search}
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\label{subsec:mrs}
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Does things.
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\subsection{Modulated Gaussian Walk}
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\label{subsec:mgw}
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Does things more efficient.
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\subsection{Localized learning}
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\label{subsec:diffusion}
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Velez describe another approach that employs
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modularity for the learning. Essentially this results in task-specific localized
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learning and functional modules for each subtask.
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\section{Comparison regarding catastrophic forgetting}
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\label{sec:comparison}
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Modulated Random Search is not at all useful for overcoming catastrophic forgetting.
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Modulated Gaussian Walk improves to that end.
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Localized learning overcomes catastrophic forgetting for small
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networks.
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\section{Conclusion}
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\section{Conclusion}
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\label{sec:concl}
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\label{sec:concl}
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Your text here...
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A second environmental feedback loop is important to tell autonomous systems
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when to learn. But the method to learn is important as well to be any use
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in a practical environment. A comparison has shown that localized learning
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can overcome catastrophic forgetting for small networks.
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% hier werden - zum Ende des Textes - die bibliographischen Referenzen
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% hier werden - zum Ende des Textes - die bibliographischen Referenzen
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