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    <title>Control on tjards</title>
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    <description>Recent content in Control on tjards</description>
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      <title>Web Shepherd: An Interactive Shepherding App (updates)</title>
      <link>https://tjards.github.io/posts/2026/web_shepherd/</link>
      <pubDate>Wed, 09 Sep 2026 19:15:53 -0400</pubDate>
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      <description>&lt;p&gt;&lt;em&gt;Updated from an original post on 14 Apr 2026.&lt;/em&gt;&lt;/p&gt;
&lt;p&gt;I recently integrated a Pull Request from &lt;a href=&#34;https://github.com/OldCrow&#34;&gt;OldCrow&lt;/a&gt; on our &lt;a href=&#34;https://tjards.github.io/web_shepherd/&#34;&gt;Web Shepherd&lt;/a&gt; web application. They have made substantial improvements to scalability, replacing the original &lt;code&gt;O(n²)&lt;/code&gt;-complex interaction loop with spatial indexing and other techniques. This extends the practical range from a &lt;strong&gt;few hundred&lt;/strong&gt; agents to a &lt;strong&gt;few thousand agents&lt;/strong&gt; while maintaining smooth real-time performance in most Web browsers.&lt;/p&gt;
&lt;p&gt;To learn more:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;The full &lt;a href=&#34;https://tjards.github.io/web_shepherd/&#34;&gt;interactive demo&lt;/a&gt; has been updated&lt;/li&gt;
&lt;li&gt;A &lt;a href=&#34;https://tjards.github.io/web_shepherd/?mode=slim&#34;&gt;slimmer version for website integration&lt;/a&gt; is available, which you may have noticed on the &lt;a href=&#34;https://tjards.github.io/&#34;&gt;homepage&lt;/a&gt;&lt;/li&gt;
&lt;li&gt;&lt;a href=&#34;https://github.com/tjards/web_shepherd&#34;&gt;Code and Documentation&lt;/a&gt; has been updated on GitHub&lt;/li&gt;
&lt;/ul&gt;
&lt;h3 id=&#34;references&#34;&gt;References&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Van Havermaet, S., Simoens, P., Landgraf, T., &amp;amp; Khaluf, Y. (2023). &lt;a href=&#34;https://doi.org/10.1098/rsos.230015&#34;&gt;Steering herds away from dangers in dynamic environments&lt;/a&gt;. &lt;em&gt;Royal Society Open Science&lt;/em&gt;, 10(5), 230015.&lt;/p&gt;</description>
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    <item>
      <title>Invited Talk at Ingenuity Labs</title>
      <link>https://tjards.github.io/posts/2026/rl_embeddings/</link>
      <pubDate>Fri, 15 May 2026 13:31:41 -0400</pubDate>
      <guid>https://tjards.github.io/posts/2026/rl_embeddings/</guid>
      <description>&lt;p&gt;I recently had the pleasure of presenting our work at the 2026 &lt;a href=&#34;https://ingenuitylabs.queensu.ca/&#34;&gt;Ingenuity Labs Research Institute&lt;/a&gt; Multi-robots Workshop. We explored a central theme across our research: when integrated within a control-theoretic framework, machine learning can enhance the performance of physical systems while preserving formal guarantees of stability and robustness. Specifically, we discussed how the swarm embeddings proposed in our &lt;a href=&#34;https://doi.org/10.1016/j.automatica.2025.112221&#34;&gt;recent work&lt;/a&gt; can be reframed as equilibrium manifolds to ensure swarms can maintain coherence and stability while learning to adapt to their environment.&lt;/p&gt;</description>
    </item>
    <item>
      <title>Multi-agent Coordination Simulator</title>
      <link>https://tjards.github.io/posts/2025/m-a_s/</link>
      <pubDate>Sun, 04 May 2025 07:04:13 -0400</pubDate>
      <guid>https://tjards.github.io/posts/2025/m-a_s/</guid>
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    &lt;p&gt;
      A fully open architecture implementation of modern multi-agent coordination techniques. All agents make individual decisions based on local information only. There is no global plan.
    &lt;/p&gt;
    &lt;p&gt;
    This is an open project I use to explore new ideas, validate theoretical results, and produce data for my academic research. 
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