<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Search Algorithms on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/search-algorithms/</link><description>Recent content in Search Algorithms 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/search-algorithms/index.xml" rel="self" type="application/rss+xml"/><item><title>Wumpus World</title><link>https://terms-en.ai-term-hub.com/en/terms/wumpus_world/</link><pubDate>Sat, 18 Jul 2026 10:20:18 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/wumpus_world/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>The Wumpus World is a grid-based environment introduced in Russell and Norvig&amp;rsquo;s AI textbook. An agent must navigate the grid to find gold while avoiding pits and a Wumpus monster. The agent perceives local cues like breezes near pits or a stench near the Wumpus, requiring logical inference to map safe paths. It serves as a foundational benchmark for understanding belief states, probabilistic reasoning, and search algorithms in partially observable, stochastic settings.&lt;/p></description></item><item><title>Incremental Heuristic Search</title><link>https://terms-en.ai-term-hub.com/en/terms/incremental_heuristic_search/</link><pubDate>Sat, 18 Jul 2026 10:02:49 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/incremental_heuristic_search/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>Incremental Heuristic Search refers to algorithms that refine a candidate solution step-by-step, guided by heuristics that estimate the cost to reach the goal. Unlike exhaustive searches, these methods focus on promising paths, making them efficient for large or complex problem spaces. Common examples include Hill Climbing and Simulated Annealing. They are particularly useful when finding an optimal solution is computationally prohibitive, and a sufficiently good solution is acceptable within reasonable time constraints.&lt;/p></description></item><item><title>Admissible heuristic</title><link>https://terms-en.ai-term-hub.com/en/terms/admissible_heuristic/</link><pubDate>Sat, 18 Jul 2026 09:44:54 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/admissible_heuristic/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In pathfinding and search problems, an admissible heuristic provides a lower bound on the actual cost to reach the target node. By guaranteeing that the estimated cost is always less than or equal to the real cost, algorithms like A* can ensure they find the shortest path if one exists. This property is critical for maintaining solution optimality while still leveraging heuristics to prune the search space efficiently, balancing speed and accuracy in complex graph traversals.&lt;/p></description></item></channel></rss>