<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Information Theory on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/information-theory/</link><description>Recent content in Information Theory on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/information-theory/index.xml" rel="self" type="application/rss+xml"/><item><title>Empowerment</title><link>https://terms-en.ai-term-hub.com/en/terms/empowerment/</link><pubDate>Sat, 18 Jul 2026 09:56:53 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/empowerment/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In reinforcement learning and artificial intelligence, empowerment is a intrinsic motivation metric that quantifies the amount of control an agent has over its environment. It is defined as the mutual information between the agent&amp;rsquo;s actions and the resulting future states. By maximizing empowerment, agents are driven to explore environments where they can effect meaningful change, leading to more robust and adaptive behaviors without relying solely on external reward signals.&lt;/p></description></item><item><title>Algorithmic probability</title><link>https://terms-en.ai-term-hub.com/en/terms/algorithmic_probability/</link><pubDate>Sat, 18 Jul 2026 09:45:36 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/algorithmic_probability/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Algorithmic probability, rooted in Kolmogorov complexity and Solomonoff induction, assigns higher probability to outputs generated by shorter programs. It posits that simpler explanations are more likely to be true, forming the basis for universal artificial intelligence theories. This concept links information theory with probability, suggesting that the complexity of an object is inversely proportional to its algorithmic probability, serving as a foundational principle for inductive inference.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>A theoretical measure of the likelihood that a random program will produce a specific output string.&lt;/p></description></item></channel></rss>