<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml"; xmlns="http://www.w3.org/TR/REC-html40";><head><meta http-equiv=Content-Type content="text/html; charset=utf-8"><meta name=Generator content="Microsoft Word 15 (filtered medium)"><style><!-- /* Font Definitions */ @font-face {font-family:Wingdings; panose-1:5 0 0 0 0 0 0 0 0 0;} @font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4;} @font-face {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {margin:0cm; font-size:11.0pt; font-family:"Calibri",sans-serif;} a:link, span.MsoHyperlink {mso-style-priority:99; color:blue; text-decoration:underline;} p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph {mso-style-priority:34; margin-top:0cm; margin-right:0cm; margin-bottom:0cm; margin-left:36.0pt; font-size:11.0pt; font-family:"Calibri",sans-serif;} .MsoChpDefault {mso-style-type:export-only;} @page WordSection1 {size:612.0pt 792.0pt; margin:72.0pt 72.0pt 72.0pt 72.0pt;} div.WordSection1 {page:WordSection1;} /* List Definitions */ @list l0 {mso-list-id:754589999; mso-list-type:hybrid; mso-list-template-ids:-1905736414 -1 134807555 134807557 134807553 134807555 134807557 134807553 134807555 134807557;} @list l0:level1 {mso-level-start-at:0; mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Symbol; mso-fareast-font-family:"Times New Roman"; mso-bidi-font-family:"Times New Roman";} @list l0:level2 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:"Courier New";} @list l0:level3 {mso-level-number-format:bullet; mso-level-text:\F0A7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Wingdings;} @list l0:level4 {mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Symbol;} @list l0:level5 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:"Courier New";} @list l0:level6 {mso-level-number-format:bullet; mso-level-text:\F0A7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Wingdings;} @list l0:level7 {mso-level-number-format:bullet; mso-level-text:\F0B7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Symbol;} @list l0:level8 {mso-level-number-format:bullet; mso-level-text:o; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:"Courier New";} @list l0:level9 {mso-level-number-format:bullet; mso-level-text:\F0A7; mso-level-tab-stop:none; mso-level-number-position:left; text-indent:-18.0pt; font-family:Wingdings;} ol {margin-bottom:0cm;} ul {margin-bottom:0cm;} --></style></head><body lang=EN-IN link=blue vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal>Hello everyone,</p><p class=MsoNormal>I am Vedant Shah, a pre-final year undergraduate student at BITS Pilani, India. I am primarily interested in two projects hosted by GFOSS for GSoC 2021: “Extend Deepbots to support stable-baseline and implement gym style default Reinforcement Learning Experiments” and “Extend Deepbots to support evolutionary algorithms”.</p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>A little bit on my background: I have been working in the fields of deep learning and (especially) reinforcement learning for quite some time now and have worked on / am working on several related projects and research. As a part of these, I have significant experience with working with deep learning frameworks like PyTorch, tensorflow, etc. and also with tools specific to reinforcement learning such as OpenAI gym, stable-baselines, rllib, etc. I am also a core-contributors to a pytorch first reinforcement learning library. A part from reinforcement learning, I have also worked in robotics on tasks such as navigation, motion planning and control. </p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I have always been interested in real-world reinforcement learning and specially it’s applications in robotics. IMy avid interests in real-world RL is the main driving factor behind be choosing these projects (I’ll be happy to work on any of these). Although I am not familiar with Webots *<b>yet</b>* it seems like a really actionable platform for testing out algorithms in context of robotics. I have grown familiar to deepbots over the past couple of days and am pretty confident I can pull (any of) these two projects off. </p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Currently I have a very rough plan of action in mind which includes</p><p class=MsoNormal><o:p> </o:p></p><ul style='margin-top:0cm' type=disc><li class=MsoListParagraph style='margin-left:0cm;mso-list:l0 level1 lfo1'>Getting comfortable with Webots (can be done before the actual work period begins)</li><li class=MsoListParagraph style='margin-left:0cm;mso-list:l0 level1 lfo1'>Researching upon some relevant evolutionary algorithms (for eg. which have been proved to be robust to noisy data) which can be used in context of robotics</li><li class=MsoListParagraph style='margin-left:0cm;mso-list:l0 level1 lfo1'>Start implementing those</li></ul><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>For the stable-baselines project, I am already familiar and have used stable-baselines before and directly jump to integrating it once I am familiar Webots (again, this can be done before the actual work period begins). I am aware that these plan of action is not very detailed and is very unrefined. So I’d like to get in touch with the mentors <span style='font-size:10.5pt;font-family:"Arial",sans-serif;color:#202122;background:white'>Manos Kirtas, Konstantinos Tsampazis, Nikolaos Passalis to discuss the project further. Looking forward to hearing from you soon!<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Arial",sans-serif;color:#202122;background:white'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Arial",sans-serif;color:#202122;background:white'>Regards,<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Arial",sans-serif;color:#202122;background:white'>Vedant<o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Sent from <a href="https://go.microsoft.com/fwlink/?LinkId=550986";>Mail</a> for Windows 10</p><p class=MsoNormal><o:p> </o:p></p></div></body></html>
---- Λαμβάνετε αυτό το μήνυμα απο την λίστα: Λίστα αλληλογραφίας και συζητήσεων που απευθύνεται σε φοιτητές developers \& mentors έργων του Google Summer of Code - A discussion list for student developers and mentors of Google Summer of Code projects., https://lists.ellak.gr/gsoc-developers/listinfo.html Μπορείτε να απεγγραφείτε από τη λίστα στέλνοντας κενό μήνυμα ηλ. ταχυδρομείου στη διεύθυνση <gsoc-developers+unsubscribe [ at ] ellak [ dot ] gr>.