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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Romain Laroche</author_name><author_url>https://www.microsoft.com/en-us/research/people/rolaroch/</author_url><title>The complex negotiation dialogue game - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="a8Hl6Ni6Wq"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/complex-negotiation-dialogue-game/"&gt;The complex negotiation dialogue game&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/complex-negotiation-dialogue-game/embed/#?secret=a8Hl6Ni6Wq" width="600" height="338" title="&#x201C;The complex negotiation dialogue game&#x201D; &#x2014; Microsoft Research" data-secret="a8Hl6Ni6Wq" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>This position paper formalises an abstract model for complex negotiation dialogue. This model is to be used for the benchmark of optimisation algorithms ranging from Reinforcement Learning to Stochastic Games, through Transfer Learning, One-Shot Learning or others.</description></oembed>
