<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Explainability on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/explainability/</link><description>Recent content in Explainability 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/explainability/index.xml" rel="self" type="application/rss+xml"/><item><title>Hybrid intelligent system</title><link>https://terms-en.ai-term-hub.com/en/terms/hybrid_intelligent_system/</link><pubDate>Sat, 18 Jul 2026 10:01:39 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/hybrid_intelligent_system/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>A Hybrid Intelligent System (HIS) merges different AI paradigms, typically combining connectionist approaches like neural networks with symbolic methods like expert systems or fuzzy logic. This integration aims to leverage the learning capability and pattern recognition of neural networks alongside the interpretability, reasoning, and rule-based decision-making of symbolic systems. HIS is particularly valuable in domains requiring both high accuracy and explainable decisions, such as medical diagnosis or autonomous driving.&lt;/p></description></item></channel></rss>