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<span class="CEURVOLNR">Vol-XXX</span> <br>
<span class="CEURURN">urn:nbn:de:0074-XXX-C</span>
<p class="unobtrusive copyright" style="text-align: justify">Copyright &copy; 2020 for
the individual papers by the papers' authors. 
Copyright &copy; <span class="CEURPUBYEAR">2020</span> for the volume
as a collection by its editors.
This volume and its papers are published under the
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<A HREF="https://creativecommons.org/licenses/by/4.0/">(<span class="CEURLIC">CC BY 4.0</span>)</A>.</p>
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<h1><a href="https://www.aisafetyw.org/"><span class="CEURVOLACRONYM">AISafety 2020</span></a><br>
<span class="CEURVOLTITLE">The IJCAI-PRICAI-20 Workshop on Artificial Intelligence Safety</span></h1>
<br>

<h3>
<span class="CEURFULLTITLE">Workshop on Artificial Intelligence Safety 2020</span><br>
co-located with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (<span class="CEURCOLOCATED">IJCAI-PRICAI-20</span>)
</h3>
<h3><span class="CEURLOCTIME">Yokohama, Japan, January, 2021</span>.</h3>
<br>
<b> Edited by </b>
<p>


</p><h3>
   <span class="CEURVOLEDITOR">Hu&aacute;scar Espinoza</span> *<br>
   <span class="CEURVOLEDITOR">John McDermid</span> **<br>
   <span class="CEURVOLEDITOR">Xiaowei Huang</span> ***<br>
   <span class="CEURVOLEDITOR">Mauricio Castillo-Effen</span> ****<br>
   <span class="CEURVOLEDITOR">Xin Cynthia Chen</span> *****<br>
   <span class="CEURVOLEDITOR">Jos&eacute; Hern&aacute;ndez-Orallo</span> ******<br>
   <span class="CEURVOLEDITOR">Se&aacute;n &Oacute; h&Eacute;igeartaigh</span> *******<br>
   <span class="CEURVOLEDITOR">Richard Mallah</span> ********<br>
   <br>

</h3>

*  Commissariat à l´Energie Atomique, France<br>
**  University of York, United Kingdom<br>
*** University of Liverpool, United Kingdom<br>
**** Lockheed Martin, USA<br>
***** University of Hong Kong, China<br>
****** Universitat Polit&egrave;cnica de Val&egrave;ncia,  Spain<br>
******* University of Cambridge, United Kingdom<br>
******** Future of Life Institute, USA<br>
    <br>

<hr>

<br><br><br>


<div class="CEURTOC">
<h2> Table of Contents </h2>


<ul>
<li id="preface">
<A href="preface.pdf">Preface</A><BR><BR>
</li>
</ul>


<h3><span class="CEURSESSION">Session 1: Adversarial Machine Learning</span></h3>

<ul>

<li id="paper_4"><a href="paper_4.pdf">
<span class="CEURTITLE">Understanding the One Pixel Attack: Propagation Maps and Locality Analysis</span></a><br>
<span class="CEURAUTHOR">Danilo Vasconcellos Vargas</span>,
<span class="CEURAUTHOR">Jiawei Su</span>
</li>

<li id="paper_8"><a href="paper_8.pdf">
<span class="CEURTITLE">Error-Silenced Quantization: Bridging Robustness and Compactness</span></a><br>
<span class="CEURAUTHOR">Zhicong Tang</span>,
<span class="CEURAUTHOR">Yinpeng Dong</span>,
<span class="CEURAUTHOR">Hang Su</span>
</li>

<li id="paper_1"><a href="paper_1.pdf">
<span class="CEURTITLE">Evolving Robust Neural Architectures to Defend from Adversarial Attacks</span></a><br>
<span class="CEURAUTHOR">Shashank Kotyan</span>,
<span class="CEURAUTHOR">Danilo Vasconcellos Vargas</span>
</li>

</ul>


<h3><span class="CEURSESSION">Session 2: AI Safety Landscape </span></h3>

<ul>
<li id="paper_7"><a href="paper_7.pdf">
<span class="CEURTITLE">Safety of Artificial Intelligence: A Collaborative Model</span></a><br>
<span class="CEURAUTHOR">John McDermid</span>,
<span class="CEURAUTHOR">Yan Jia</span>
</li>
</ul>


<h3><span class="CEURSESSION">Session 3: Safe and Value-Aligned Learning in Decision Making</span></h3>

<ul>
<li id="paper_14"><a href="paper_14.pdf">
<span class="CEURTITLE">Choice Set Misspeciﬁcation in Reward Inference</span></a><br>
<span class="CEURAUTHOR">Rachel Freedman</span>,
<span class="CEURAUTHOR">Rohin Shah</span>,
<span class="CEURAUTHOR">Anca Dragan</span>
</li>

<li id="paper_13"><a href="paper_13.pdf">
<span class="CEURTITLE">Safety Augmentation in Decision Trees</span></a><br>
<span class="CEURAUTHOR">Sumanta Dey</span>,
<span class="CEURAUTHOR">Pallab Dasgupta</span>,
<span class="CEURAUTHOR">Briti Gangopadhyay</span>
</li>


<li id="paper_15"><a href="paper_15.pdf">
<span class="CEURTITLE">Aligning with Heterogenous Preferences for Kidney Exchange</span></a><br>
<span class="CEURAUTHOR">Rachel Freedman</span>
</li>

</ul>

<h3><span class="CEURSESSION">Session 4: DNN Testing and Runtime Monitoring </span></h3>

<ul>

<li id="paper_18"><a href="paper_18.pdf">
<span class="CEURTITLE">Is Uncertainty Quantification in Deep Learning Sufficient for Out-of-Distribution Detection?</span></a><br>
<span class="CEURAUTHOR">Adrian Schwaiger</span>,
<span class="CEURAUTHOR">Poulami Sinhamahapatra</span>,
<span class="CEURAUTHOR">Jens Gansloser</span>,
<span class="CEURAUTHOR">Karsten Roscher</span>
</li>

<li id="paper_19"><a href="paper_19.pdf">
<span class="CEURTITLE">DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning</span></a><br>
<span class="CEURAUTHOR">Samet Demir</span>,
<span class="CEURAUTHOR">Hasan Ferit Eniser</span>,
<span class="CEURAUTHOR">Alper Sen</span>
</li>


<li id="paper_24"><a href="paper_24.pdf">
<span class="CEURTITLE">A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications</span></a><br>
<span class="CEURAUTHOR">Fabio Arnez</span>,
<span class="CEURAUTHOR">Huascar Espinoza</span>,
<span class="CEURAUTHOR">Ansgar Radermacher</span>,
<span class="CEURAUTHOR">François Terrier</span>
</li>


<li id="paper_3"><a href="paper_3.pdf">
<span class="CEURTITLE">Increasing the Trustworthiness of Deep Neural Networks via Accuracy Monitoring</span></a><br>
<span class="CEURAUTHOR">Zhihui Shao</span>,
<span class="CEURAUTHOR">Jianyi Yang</span>,
<span class="CEURAUTHOR">Shaolei Ren</span>
</li>


</ul>


<h3><span class="CEURSESSION">Poster Papers </span></h3>

<ul>

<li id="paper_20"><a href="paper_20.pdf">
    <span class="CEURTITLE">Robustness as Inherent Property of Datapoints</span></a>
  (short paper)
  <br>
<span class="CEURAUTHOR">Catalin-Andrei Ilie</span>,
<span class="CEURAUTHOR">Marius Popescu</span>,
<span class="CEURAUTHOR">Alin Stefanescu</span>
</li>


<li id="paper_25"><a href="paper_25.pdf">
    <span class="CEURTITLE">Towards Safe and Reliable Robot Task Planning</span></a>
  (short paper)
  <br>
<span class="CEURAUTHOR">Snehasis Banerje</span>
</li>


<li id="paper_21"><a href="paper_21.pdf">
<span class="CEURTITLE">Extracting Money from Causal Decision Theorists</span></a><br>
<span class="CEURAUTHOR">Caspar Oesterheld</span>,
<span class="CEURAUTHOR">Vincent Conitzer</span>
</li>


<li id="paper_11"><a href="paper_11.pdf">
<span class="CEURTITLE">Ethically Compliant Planning in Moral Autonomous Systems</span></a><br>
<span class="CEURAUTHOR">Justin Svegliato</span>,
<span class="CEURAUTHOR">Samer Nashed</span>,
<span class="CEURAUTHOR">Shlomo Zilberstein</span>
</li>


<li id="paper_6"><a href="paper_6.pdf">
<span class="CEURTITLE">Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers</span></a><br>
<span class="CEURAUTHOR">Andrey Morozov</span>,
<span class="CEURAUTHOR">Emil Valiev</span>,
<span class="CEURAUTHOR">Michael Beyer</span>,
<span class="CEURAUTHOR">Kai Ding</span>,
<span class="CEURAUTHOR">Lydia Gauerhof</span>,
<span class="CEURAUTHOR">Christoph Schorn</span>
</li>


</ul>


</div>


<hr>
<span class="unobtrusive">
2020-07-15: submitted by Xin Cynthia Chen,
            metadata incl. bibliographic data published under <A HREF="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons CC0</A><br>
<span class="CEURPUBDATE">2020-07-15</span>: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)
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