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@@ -121,10 +121,10 @@ <h1 class="title is-1 publication-title">DNT-RL: Soccer Behavior Learning in Par
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<div class="container is-max-desktop">
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<div class="hero-body">
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<video id="teaser" autoplay muted loop playsinline height="100%">
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<source src="./static/videos/striker.webm" type="video/webm">
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<source src="./static/videos/teaser.mp4" type="video/mp4">
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</video>
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<h2 class="subtitle has-text-centered">
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<span class="ddnt-rl">DNT-RL</span> learning a walk to point policy with 64 parallel agents.
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<span class="dnerf">DNT-RL</span> learning a walk to point policy with 64 parallel agents.
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</h2>
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</div>
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</div>
@@ -199,7 +199,7 @@ <h2 class="title is-3">Abstract</h2>
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time of each behavior.
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</p>
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<p>
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In this paper, we introduce t <span class="ddnt-rl">DNT-RL</span>, a framework designed for the efficient
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In this paper, we introduce t <span class="dnerf">DNT-RL</span>, a framework designed for the efficient
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training of 2D RL behaviors
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using parallel training with multiple environments. The framework integrates a physics-based simulation
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with a standardized way of training behaviors, supporting parallelized and GPU-accelerated training to

static/videos/teaser.mp4

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