Multiagent Cooperative Learning Strategies for Pursuit-Evasion Games

<div class="floats-full-page floats-full-page-other"><h2>Algorithm 1</h2><div class="floats-full-page-caption"><div>Random movement algorithm.</div></div><div class="floats-full-page-content"><table class="algorithm-group"><tr><td><table class="algorithm" id="alg1"><tr><td colspan="2">(1) <b>while </b>true <b>do</b></td></tr><tr><td colspan="2">(2) <i> </i>next location <i>←</i> generates randomly a location nearby the evader</td></tr><tr><td colspan="2">(3)   <i>  </i><b>if</b> next location has an obstacle <b>then</b></td></tr><tr><td colspan="2">(4)     <i> </i>next location <i>←</i> generates randomly a new location nearby the evader</td></tr><tr><td colspan="2">(5)   <i>  </i><b>end if</b></td></tr><tr><td colspan="2">(6) <b>end while</b></td></tr></table></td></tr></table></div></div>

Algorithm 1 | Multiagent Cooperative Learning Strategies for Pursuit-Evasion Games

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Algorithm 1: Multiagent Cooperative Learning Strategies for Pursuit-Evasion Games

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Algorithm 1

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<p><em>Mathematical Problems in Engineering</em> is a broad-based journal publishing&nbsp;results of rigorous engineering research across all disciplines, carried out using mathematical tools.</p>


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<p>Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.</p>


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