AI Reference 017 Classical AI & Machine Learning Wikipedia guided Primary sources linked

Search Algorithms in Artificial Intelligence

Definition

AI search algorithms explore possible states or actions in order to find paths, plans or solutions. Classical examples include breadth-first search, depth-first search and A*.

What is search in AI?

Search in AI means exploring a space of possible states or actions to find a path, solution or plan. A state can represent a puzzle configuration, a board position, a route through a map or any other description of a problem at one moment.

Uninformed and informed search

Breadth-first search explores level by level; depth-first search follows one branch deeply before backtracking. Informed methods use additional knowledge. A* search, introduced in the late 1960s, combines the cost already paid with a heuristic estimate of the remaining cost.

Why search still matters

Search is not replaced by machine learning. Game-playing programs, route planning, scheduling, theorem proving and agent systems still use search when they must evaluate alternatives. Modern models can propose candidate actions, while conventional search or planning algorithms can organize and verify them.

Related terms, defined

Classical AI & Machine Learning Heuristics and Problem Solving A heuristic is an estimate or rule used to guide search toward promising states without exhaustively checking every alternative. Classical AI & Machine Learning Knowledge Representation Knowledge representation studies how facts, relations, rules and concepts can be encoded so a computer system can reason over them. Classical AI & Machine Learning Expert Systems Expert systems are narrow rule-based programs that separate a knowledge base from an inference mechanism to reproduce parts of specialist decision-making. Classical AI & Machine Learning ELIZA and Early Conversational Programs ELIZA, created by Joseph Weizenbaum in the 1960s, used pattern matching and scripted text transformations to simulate conversation without modern statistical language understanding. Classical AI & Machine Learning SHRDLU and Language in a Blocks World SHRDLU, developed by Terry Winograd around 1968–1970, accepted natural-language instructions about a small simulated blocks world and combined language parsing with a symbolic world model.

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.

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