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<p class="MsoPlainText">Dear Colleagues we would like to cordially invite you to submit to the following special session in the coming IJCNN 2017 conference<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoTitleCxSpFirst"><span style="font-size:14.0pt">IEEE International Joint Conference on Neural Networks (<span style="color:#1F497D"><a href="http://www.ijcnn.org/paper-submission">IJCNN 2017</a></span>)<o:p></o:p></span></p>
<p class="MsoTitleCxSpLast" style="margin-bottom:6.0pt;mso-add-space:auto"><b><u><span style="font-size:14.0pt">Special Session on: Deep and Reinforcement Learning (DRL)<o:p></o:p></span></u></b></p>
<p class="MsoNormal">RL does not lend itself naturally to deep learning from an MDP framework perspective, and currently there is no uniformed approach to combine deep learning with realistic reinforcement learning despite very successful applications in virtual
and gaming environments. Examples of important open questions are: <o:p></o:p></p>
<p class="MsoListParagraphCxSpFirst" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>How to make the state-action learning process deep?
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>How to make the architecture of an RL system appropriate to deep learning without compromising the interactivity of the system?
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>How to make the learning suitable for a realistic scenario?
<o:p></o:p></p>
<p class="MsoListParagraphCxSpLast" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>How to infuse a self-reflective process in the system?
<o:p></o:p></p>
<p class="MsoNormal" style="margin-top:6.0pt">Although recently there have been important advances in dealing with these issues, they are still scattered and with no overarching framework that promote them in a well-defined and natural way. This special session
will provide a unique platform for researchers from Deep Learning and Reinforcement Learning communities to share their research experience towards a uniformed Deep Reinforcement Learning (DRL) framework in order to allow this important interdisciplinary branch
to take-off on solid grounds. It will touch on the potential benefits of the different approaches to combine RL and DL. The aim is to bring more focus onto the potential of infusing reinforcement learning framework with deep learning capabilities that could
allow it to deal more effectively with present applications such as realistic robotics, online streamed data processing that involves actions. Contribution is invited from all deep learning, reinforcement learning and deep reinforcement learning research.<o:p></o:p></p>
<h1 style="margin-top:0cm;mso-add-space:auto;line-height:normal"><span style="font-size:12.0pt">Scope and Topics<span style="color:#1F497D"><o:p></o:p></span></span></h1>
<p class="MsoListParagraphCxSpFirst" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Novel RL Techniques suitable for physical systems<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Novel Deep and/or RL Algorithms<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Novel Deep and RL Neural Architectures<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Adaptation of existing RL Techniques for Deep Learning
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Optimization and convergence proofs for DRL algorithms
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deeply Hierarchical RL<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deep and/or RL architecture and algorithms for Control<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deep and/or RL architecture and algorithms for Robotics<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deep and/or RL architecture and algorithms for Time Series<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deep and/or RL architecture and algorithms for Big Streamed Data Processing<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Deep and/or RL architecture and algorithms for Optimizing Governmental Policy
<o:p></o:p></p>
<p class="MsoListParagraphCxSpLast" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Other Deep and/or RL theory and application…<o:p></o:p></p>
<h1 style="margin-top:0cm;mso-add-space:auto;line-height:normal"><span style="font-size:11.0pt">Important Dates<o:p></o:p></span></h1>
<p class="MsoListParagraphCxSpFirst" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Paper submission: November 15, 2016
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Paper decision notification: January 20, 2017
<o:p></o:p></p>
<p class="MsoListParagraphCxSpLast" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level1 lfo2">
<![if !supportLists]><span style="font-family:"Calibri","sans-serif""><span style="mso-list:Ignore">-<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span dir="LTR"></span>Camera-ready submission: February 20, 2017<o:p></o:p></p>
<h1 style="margin-top:0cm;mso-add-space:auto;line-height:normal"><span style="font-size:11.0pt">Organizers<o:p></o:p></span></h1>
<p class="MsoListParagraphCxSpFirst" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-align:justify;line-height:normal">
Abdulrahman Altahhan(<a href="mailto:ab8556@coventry.ac.uk">ab8556@coventry.ac.uk</a>), COVENTRY UNIVERSITY, UK.
<o:p></o:p></p>
<p class="MsoListParagraphCxSpMiddle" style="margin-bottom:0cm;margin-bottom:.0001pt;mso-add-space:auto;text-align:justify;line-height:normal">
Vasile Palade, COVENTRY UNIVERSITY, UK. <o:p></o:p></p>
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Roozbeh Razavi-Far, University of Windsor, Canada.<o:p></o:p></p>
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<p style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;" data-mce-style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;"><br></p><p style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;" data-mce-style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;"><br data-mce-bogus="1"></p><p style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;" data-mce-style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;"><br></p><p style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;" data-mce-style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;">University of the Year 2015</p><p style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;" data-mce-style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;">Source: Times Higher Education Awards 2015</p><p style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;" data-mce-style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;"><br></p><p style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;" data-mce-style="color: #0080d4; font-family: 'Arial', 'sans-serif'; font-size: 18px; line-height: 20px; margin: 0; font-weight: bold;">Modern University of the Year<br> 2014 | 2015 | 2016</p><p style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;" data-mce-style="margin: 4px 0; color: #0080d4; font-family: 'Arial','sans-serif'; font-size: 12px; line-height: 16px;">Source: The Times and The Sunday Times Good University Guide 2014, 2015, 2016</p><p style="font-family: 'Arial', 'sans-serif'; font-size: 6px; line-height: 6px;" data-mce-style="font-family: 'Arial', 'sans-serif'; font-size: 6px; line-height: 6px;"> </p><p style="margin: 20px 0 0 0; line-height: 11px; font-family: 'Arial', 'sans-serif'; font-size: 9px;" data-mce-style="margin: 20px 0 0 0; line-height: 11px; font-family: 'Arial', 'sans-serif'; font-size: 9px;">NOTICE <br> <br> This message and any files transmitted with it is intended for the addressee only and may contain information that is confidential or privileged. Unauthorised use is strictly prohibited. If you are not the addressee, you should not read, copy, disclose or otherwise use this message, except for the purpose of delivery to the addressee. <br> <br> Any views or opinions expressed within this e-mail are those of the author and do not necessarily represent those of Coventry University.</p></body>
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