<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Symbolic AI on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/symbolic-ai/</link><description>Recent content in Symbolic AI 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/symbolic-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>Knowledge-based systems</title><link>https://terms-en.ai-term-hub.com/en/terms/knowledge_based_systems/</link><pubDate>Sat, 18 Jul 2026 10:04:10 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/knowledge_based_systems/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Knowledge-based systems (KBS) are a branch of artificial intelligence that incorporates specific domain knowledge into a computer system to perform tasks that typically require human expertise. They consist of two main components: a knowledge base containing facts and rules, and an inference engine that applies logical reasoning to derive new information or solutions. Unlike traditional software, KBS can explain their reasoning process, making them valuable in fields like medicine, engineering, and finance where transparency and expert-level decision-making are critical.&lt;/p></description></item><item><title>Explanation-based learning</title><link>https://terms-en.ai-term-hub.com/en/terms/explanation_based_learning/</link><pubDate>Sat, 18 Jul 2026 09:57:38 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/explanation_based_learning/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>EBL combines symbolic reasoning with machine learning to accelerate the learning process. Instead of relying on large datasets, it takes a single positive example and uses a pre-existing domain theory to explain why the example belongs to the target concept. This explanation is then operationalized into a general rule that can be applied to future instances. It is particularly useful when data is scarce but domain knowledge is abundant, allowing for rapid acquisition of skills.&lt;/p></description></item><item><title>Automated Mathematician</title><link>https://terms-en.ai-term-hub.com/en/terms/automated_mathematician/</link><pubDate>Sat, 18 Jul 2026 09:47:03 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/automated_mathematician/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>An Automated Mathematician utilizes machine learning and symbolic reasoning to explore mathematical spaces beyond human intuition. These systems can generate hypotheses, verify proofs, and find patterns in complex structures. They assist researchers by handling tedious calculations or suggesting novel directions in number theory, geometry, or algebra. This field represents the intersection of formal verification, logic programming, and neural networks, aiming to augment human mathematical creativity.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>An AI system designed to discover new mathematical theorems, conjectures, or proofs through computational search and reasoning.&lt;/p></description></item></channel></rss>