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<h1>Stage M1R 2017</h1>
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<h2>Pointeurs</h2>
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<h4>RL</h4>
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<ul>
<li class="level1"> cours M1:  <a href="/lib/exe/fetch.php?media=m1r2017:cm1m22016-17.pdf" class="media mediafile mf_pdf" title="m1r2017:cm1m22016-17.pdf (6.6 MB)">MDP et planif</a>, <a href="/lib/exe/fetch.php?media=m1r2017:cm4a2016rl.pdf" class="media mediafile mf_pdf" title="m1r2017:cm4a2016rl.pdf (9.3 MB)">RL</a>  </li>
<li class="level1"> cours David Silver : http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html</li>
<li class="level1"> livre de Sutton mis à jour:  https://webdocs.cs.ualberta.ca/~sutton/book/bookdraft2016sep.pdf</li>
</ul>
<ul>
<li class="level1 node"> Multi-Agent RL : <ul>
<li class="level3"> en premier, lire le chapitre 4 de https://tel.archives-ouvertes.fr/file/index/docid/362529/filename/these_matignon.pdf</li>
<li class="level3"> puis lire http://liris.cnrs.fr/laetitia.matignon/index/matignon2012KER.pdf</li>
</ul>
</li>
</ul>
<ul>
<li class="level1 node"> Travaux de De Hauwere: Learning multi-agent state space representations<ul>
<li class="level3"> http://www.aamas-conference.org/Proceedings/aamas2010/pdf/01%20Full%20Papers/15_02_FP_0421.pdf</li>
<li class="level3"> https://ai.vub.ac.be/ALA2012/downloads/paper5.pdf</li>
</ul>
</li>
</ul>

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<h4>Construction de représentations en RL</h4>
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<p>
Approches par généralisation (<em>Apply knowledge to unseen but similar states</em>)
</p>
<ul>
<li class="level1"> Tile Coding et versions adaptatives <a href="/lib/exe/fetch.php?tok=3a8204&media=http%3A%2F%2Fwww.cs.utexas.edu%2F~ai-lab%2Fpubs%2Fwhitesontr07.ps" class="media mediafile mf_ps" title="http://www.cs.utexas.edu/~ai-lab/pubs/whitesontr07.ps">adaptative_tile_coding [Whiteson,2007] </a> et <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:lin_wright_-2010-_evolutionary_tile_coding.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:lin_wright_-2010-_evolutionary_tile_coding.pdf">evolutionary_tile_coding [Lin,2010] </a></li>
<li class="level1"> <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:bauman--gngq.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:bauman--gngq.pdf"> GNG Q [Baumann,2012]</a> + <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:bauman-2013-gngqpwt.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:bauman-2013-gngqpwt.pdf"> slides </a></li>
<li class="level1"> Vector Quantization  <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:lee-2004-tdavq.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:lee-2004-tdavq.pdf"> TD AVQ [Lee2004]</a></li>
<li class="level1"> Combinaison de growing neural gaz GNG et Q-Learning pour discrétisation adaptative de l'espace d'états: <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:vieira2013tdgng.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:vieira2013tdgng.pdf">TD-GNG [Vieira, Adeodato, Goncalves,2013]</a></li>
<li class="level1"> <a href="/lib/exe/fetch.php?media=wiki:consap:biblio:kuipers_provost-2006-developing_navigation_behavior_through_self-organizing_distinctive_state_abstraction.pdf" class="media mediafile mf_pdf wikilink2" title="wiki:consap:biblio:kuipers_provost-2006-developing_navigation_behavior_through_self-organizing_distinctive_state_abstraction.pdf">Self-Organizing Distinctive-State Abstraction (SODA) [Kuipers,2006] </a></li>
</ul>

</div>

<h4>App Constructiviste</h4>
<div class="level4">
<ul>
<li class="level1"> Thèse S. Mazac: https://tel.archives-ouvertes.fr/tel-01310583/file/TH2015MazacSebastien.pdf</li>
</ul>

</div>

<h4>RL et Inspirations Constructivistes</h4>
<div class="level4">
<ul>
<li class="level1"> Intrinsically Motivated RL [Singh2005] https://web.eecs.umich.edu/~baveja/Papers/FinalNIPSIMRL.pdf</li>
</ul>

</div>

<h2>Mémentos</h2>
<div class="level2">

<p>
A lire :
</p>
<ul>
<li class="level1"> https:<em>ai.vub.ac.be/ALA2012/downloads/paper4.pdf
   * http:</em>ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/39192/HolmesParkerChristopherG2013.pdf;sequence=1</li>
</ul>

</div>

<h3>App Constructiviste</h3>
<div class="level3">
<ul>
<li class="level1"> <a href="/doku.php?id=compte-rendu-etat-art-these" class="wikilink1" title="compte-rendu-etat-art-these" data-wiki-id="compte-rendu-etat-art-these"> Etat de l'art (Thèse S. Mazac)</a></li>
</ul>

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<h4>Multi-agents</h4>
<div class="level4">
<ul>
<li class="level1"> <a href="/doku.php?id=memento-learning-multi-agent-state-space-representations" class="wikilink1" title="memento-learning-multi-agent-state-space-representations" data-wiki-id="memento-learning-multi-agent-state-space-representations"> Learning multi-agent state space representations (CQLearning)</a></li>
<li class="level1"> <a href="/doku.php?id=memento-processus-decisionnels-de-markov-et-systemes-multiagents" class="wikilink1" title="memento-processus-decisionnels-de-markov-et-systemes-multiagents" data-wiki-id="memento-processus-decisionnels-de-markov-et-systemes-multiagents"> Processus décisionnels de Markov et systèmes multiagents (Thèse L. Matignon)</a></li>
<li class="level1"> <a href="/doku.php?id=memento-independent-reinforcement-learners-cooperative-markov-games:a-survey-regarding-coordination-problems" class="wikilink1" title="memento-independent-reinforcement-learners-cooperative-markov-games:a-survey-regarding-coordination-problems" data-wiki-id="memento-independent-reinforcement-learners-cooperative-markov-games:a-survey-regarding-coordination-problems"> Independent reinforcement learners in cooperative Markov games: a survey regarding coordination problems (A terminer)</a></li>
<li class="level1"> <a href="/doku.php?id=memento-context-sensitive-reward-shaping-for-sparse-inter-action-multi-agent-systems" class="wikilink1" title="memento-context-sensitive-reward-shaping-for-sparse-inter-action-multi-agent-systems" data-wiki-id="memento-context-sensitive-reward-shaping-for-sparse-inter-action-multi-agent-systems"> Context-Sensitive Reward Shaping for Sparse Inter-action Multi-Agent Systems</a></li>
</ul>

</div>

<h4>Inspirations Constructivistes</h4>
<div class="level4">
<ul>
<li class="level1"> <a href="/doku.php?id=memento-intrinsically-motivated-rl" class="wikilink1" title="memento-intrinsically-motivated-rl" data-wiki-id="memento-intrinsically-motivated-rl"> Intrinsically Motivated RL [Singh2005]</a></li>
</ul>

</div>

<h3>Value function approximation</h3>
<div class="level3">
<ul>
<li class="level1"> <a href="/doku.php?id=memento-value-function-approximation" class="wikilink1" title="memento-value-function-approximation" data-wiki-id="memento-value-function-approximation"> Quelques infos</a></li>
</ul>

</div>

<h3>Temporal Difference - Growing Neural Gas</h3>
<div class="level3">
<ul>
<li class="level1"> <a href="/doku.php?id=memento-td-gng" class="wikilink1" title="memento-td-gng" data-wiki-id="memento-td-gng"> TD-GNG</a></li>
</ul>

</div>

<h2>Réflexions</h2>
<div class="level2">
<ul>
<li class="level1"> <a href="/doku.php?id=reflexion-gng-qc" class="wikilink1" title="reflexion-gng-qc" data-wiki-id="reflexion-gng-qc"> CQ-Learning et TD-GNG</a></li>
</ul>

</div>

<h2>Comptes-rendu de réunion</h2>
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<p>
Dossier contenant les slides présentés lors des réunions :
 slides
</p>
<ul>
<li class="level1"> <a href="/doku.php?id=reu02-03-17" class="wikilink1" title="reu02-03-17" data-wiki-id="reu02-03-17">02/03/17</a></li>
<li class="level1"> <a href="/doku.php?id=reu14-03-17" class="wikilink1" title="reu14-03-17" data-wiki-id="reu14-03-17">14/03/17</a></li>
</ul>

</div>

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