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		<title>Kumar et al 2019a - Revision history</title>
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		<updated>2026-04-21T17:47:57Z</updated>
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		<id>https://www.scipedia.com/wd/index.php?title=Kumar_et_al_2019a&amp;diff=201229&amp;oldid=prev</id>
		<title>Scipediacontent: Scipediacontent moved page Draft Content 379122524 to Kumar et al 2019a</title>
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				<updated>2021-02-02T03:07:24Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_379122524&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 379122524&quot;&gt;Draft Content 379122524&lt;/a&gt; to &lt;a href=&quot;/public/Kumar_et_al_2019a&quot; title=&quot;Kumar et al 2019a&quot;&gt;Kumar et al 2019a&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 03:07, 2 February 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>https://www.scipedia.com/wd/index.php?title=Kumar_et_al_2019a&amp;diff=201228&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around comme...&quot;</title>
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				<updated>2021-02-02T03:07:18Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around comme...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around commercial airports. We develop a method to learn the rules of air traffic control from real data as a cost function via maximum entropy inverse reinforcement learning. This cost function is used as a penalty for a search-based motion planning method that discretizes both the control and the state space. We illustrate the methodology by showing that our approach can learn to imitate the airport arrival routes and separation rules of dense commercial air traffic. The resulting trajectories are shown to be safe, feasible, and efficient.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://arxiv.org/abs/1903.10525 http://arxiv.org/abs/1903.10525]&lt;br /&gt;
&lt;br /&gt;
* [http://arxiv.org/pdf/1903.10525 http://arxiv.org/pdf/1903.10525]&lt;br /&gt;
&lt;br /&gt;
* [http://xplorestaging.ieee.org/ielx7/8957008/8967518/08968460.pdf?arnumber=8968460 http://xplorestaging.ieee.org/ielx7/8957008/8967518/08968460.pdf?arnumber=8968460],&lt;br /&gt;
: [http://dx.doi.org/10.1109/iros40897.2019.8968460 http://dx.doi.org/10.1109/iros40897.2019.8968460]&lt;br /&gt;
&lt;br /&gt;
* [https://dblp.uni-trier.de/db/conf/iros/iros2019.html#TolstayaR0K19 https://dblp.uni-trier.de/db/conf/iros/iros2019.html#TolstayaR0K19],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/3003652570 https://academic.microsoft.com/#/detail/3003652570]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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