AI Reference 026 Classical AI & Machine Learning Wikipedia guided Primary sources linked

Genetic Algorithms

Definition

Genetic algorithms are optimization methods inspired by evolutionary selection, iteratively varying and selecting candidate solutions according to a fitness function.

What is a genetic algorithm?

A genetic algorithm is an optimization method inspired by biological evolution. It maintains a population of candidate solutions, measures each candidate with a fitness function, and produces new candidates through selection, crossover and mutation.

How the search progresses

Candidates that score well are more likely to contribute to later generations. Crossover recombines parts of candidate representations, while mutation introduces random variation. Over many generations, the population can move toward better solutions.

Where genetic algorithms fit

John Holland helped formalize genetic algorithms in the 1960s and 1970s. They are useful when a problem has a large search space and a workable fitness function but no convenient gradient. They are optimization algorithms, not models that understand the problem in a human sense.

Related terms, defined

Classical AI & Machine Learning Reinforcement Learning Reinforcement learning trains an agent by interaction: actions change an environment, rewards provide feedback and the agent learns a policy intended to maximize cumulative reward. Classical AI & Machine Learning Supervised Learning Supervised learning trains a model from examples paired with known labels or target values. Classification and regression are common supervised tasks. Classical AI & Machine Learning Unsupervised Learning Supervised learning trains a model from examples paired with known labels or target values. Classification and regression are common supervised tasks. Classical AI & Machine Learning Artificial Intelligence vs Machine Learning Artificial intelligence is the broader field concerned with systems performing tasks associated with intelligent behavior; machine learning is a major subfield in which systems learn patterns from data. Classical AI & Machine Learning Symbolic AI Symbolic AI represents knowledge with explicit symbols, rules and structures, then manipulates those representations with logic, search or planning procedures.

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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