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| {% extends "Test-layout.html" %}
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| {% block content %}
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| <h1 class="text-4xl font-bold text-gray-800 mb-6">Reinforcement Learning</h1>
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| <p class="text-gray-600 text-lg mb-8">Reinforcement learning (RL) is a subfield of machine learning where an agent learns to make decisions by taking actions in an environment to maximize some cumulative reward.</p>
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| <div class="flex flex-col gap-6">
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| <div class="card p-6">
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| <h2 class="text-2xl font-semibold text-gray-800 mb-4">Core Concepts of RL</h2>
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| <div class="flex flex-wrap gap-4">
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| <a href="/agent-environment-state-test" class="algorithm-box">Agent, Environment, and State</a>
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| <a href="/action-policy-test" class="algorithm-box">Action and Policy</a>
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| <a href="/reward-value-function-test" class="algorithm-box">Reward and Value Function</a>
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| <a href="/q-learning-test" class="algorithm-box">Q-Learning</a>
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| <a href="/deep-reinforcement-learning-test" class="algorithm-box">Deep Reinforcement Learning</a>
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| </div>
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| </div>
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| </div>
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| {% endblock %} |
