// Workers AI · dad joke modeWhat did the list of AI algorithms say? "We're learning to sort things out.

This is a list of artificial intelligence algorithms, including algorithms and algorithmic methods used in artificial intelligence (AI) for search, automated reasoning, knowledge representation and reasoning, planning, machine learning, deep learning, natural language processing, computer vision, and related areas.^[1]

Search

Search algorithms

Game-tree search

Optimization

Evolutionary and bio-inspired methods

Evolutionary computation

Bio-inspired methods

Reasoning and inference

Automated reasoning

Logic

Statistical inference

Planning and navigation

Pathfinding

Motion planning

Machine learning

Ensemble learning

Classification

Clustering

Association learning

Dimensionality reduction

Neural learning

Reinforcement learning

Deep learning

Other machine learning

Natural language processing

Computer vision

Algorithmic game play

References

↑ "Artificial Intelligence (AI) Algorithms". GeeksforGeeks. July 23, 2025. Retrieved April 19, 2026.
↑ "Machine Learning Algorithms". GeeksforGeeks. January 20, 2026. Retrieved April 19, 2026.
↑ Quesada, Alberto (October 28, 2019). "5 algorithms to train a neural network". Neural Designer Blog. Artelnics. Retrieved April 20, 2026.
↑ Silver, David; et al. (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. doi:10.1038/nature16961.
↑ Silver, David; et al. (October 2017). "Mastering the game of Go without human knowledge". Nature. 550: 354–359. doi:10.1038/nature24270.
↑ Silver, David; et al. (December 2018). "A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play". Science. 362 (6419): 1140–1144. doi:10.1126/science.aar6404.
↑ Schrittwieser, Julian; et al. (December 2020). "Mastering Atari, Go, chess and shogi by planning with a learned model". Nature. 588: 604–609. arXiv:1911.08265. doi:10.1038/s41586-020-03051-4.
↑ Tesauro, Gerald (March 1995). "Temporal difference learning and TD-Gammon". Communications of the ACM. 38 (3): 58–68. doi:10.1145/203330.203343.

[1] "Artificial Intelligence (AI) Algorithms". GeeksforGeeks. July 23, 2025. Retrieved April 19, 2026.

[2] "Machine Learning Algorithms". GeeksforGeeks. January 20, 2026. Retrieved April 19, 2026.

[3] Quesada, Alberto (October 28, 2019). "5 algorithms to train a neural network". Neural Designer Blog. Artelnics. Retrieved April 20, 2026.

[silver-2016-alphago-4] Silver, David; et al. (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. doi:10.1038/nature16961.

[silver-2017-alphago-zero-5] Silver, David; et al. (October 2017). "Mastering the game of Go without human knowledge". Nature. 550: 354–359. doi:10.1038/nature24270.

[silver-2018-alphazero-6] Silver, David; et al. (December 2018). "A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play". Science. 362 (6419): 1140–1144. doi:10.1126/science.aar6404.

[schrittwieser-2020-muzero-7] Schrittwieser, Julian; et al. (December 2020). "Mastering Atari, Go, chess and shogi by planning with a learned model". Nature. 588: 604–609. arXiv:1911.08265. doi:10.1038/s41586-020-03051-4.

[tesauro-1995-td-gammon-8] Tesauro, Gerald (March 1995). "Temporal difference learning and TD-Gammon". Communications of the ACM. 38 (3): 58–68. doi:10.1145/203330.203343.

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v t e Artificial intelligence algorithms
Search	A* search algorithm Beam search Beam stack search Best-first search Breadth-first search Depth-first search General Problem Solver Iterative deepening A* Iterative deepening depth-first search Uniform-cost search
Game-tree search	Alpha–beta pruning Expectiminimax Minimax Monte Carlo tree search SSS*
Optimization	ALOPEX Bayesian optimization Conjugate gradient method Gradient descent Hill climbing Levenberg–Marquardt algorithm Quadratic unconstrained binary optimization Quasi-Newton method Simulated annealing Stochastic gradient descent
Evolutionary computation	Differential evolution Evolutionary multimodal optimization Genetic algorithm Genetic programming
Bio-inspired methods	Ant colony optimization algorithms Particle swarm optimization
Automated reasoning	Backward chaining Forward chaining Rete algorithm
Logic	DPLL algorithm Resolution (logic) WalkSAT
Statistical inference	Baum–Welch algorithm Belief propagation Expectation–maximization algorithm Forward–backward algorithm Kalman filter Markov chain Monte Carlo (MCMC) Viterbi algorithm
Pathfinding	A* D* Dijkstra's algorithm Theta*
Motion planning	Bug algorithm Dynamic window approach Graphplan Probabilistic roadmap Rapidly-exploring random tree Vector Field Histogram
Ensemble learning	AdaBoost Bootstrap aggregating BrownBoost Gradient boosting LogitBoost LPBoost Random forest Randomized weighted majority algorithm Weighted majority algorithm
Classification	Alternating decision tree C4.5 algorithm CN2 algorithm Decision tree learning Dominance-based rough set approach Genetic Algorithm for Rule Set Production ID3 algorithm k-nearest neighbors algorithm Logic learning machine Logistic regression Naive Bayes classifier Relevance vector machine RIPPER Structured kNN Support vector machine Winnow algorithm
Clustering	DBSCAN Hierarchical clustering k-means++ k-means clustering k-medoids Linde–Buzo–Gray algorithm Lloyd's algorithm OPTICS
Association learning	Apriori algorithm Eclat algorithm FP-growth algorithm
Dimensionality reduction	Diffusion map FastICA Kernel principal component analysis Manifold alignment Minimum redundancy feature selection Non-negative matrix factorization Principal component analysis Sparse PCA T-distributed stochastic neighbor embedding
Neural learning	Almeida–Pineda recurrent backpropagation Backpropagation GeneRec Generalized Hebbian algorithm Growing self-organizing map Learning vector quantization Leabra Perceptron Quickprop Rprop Self-organizing map Wake-sleep algorithm
Reinforcement learning	Actor-critic algorithm Constructing skill trees Error-driven learning Policy gradient method Prefrontal cortex basal ganglia working memory Proximal policy optimization PVLV Q-learning Skill chaining State–action–reward–state–action Temporal difference learning
Deep learning	PagedAttention vAttention
Other machine learning	Dynamic time warping IDistance Local outlier factor
Natural language processing	Byte-pair encoding Cocke–Younger–Kasami algorithm Earley parser Inside-outside algorithm
Computer vision	Canny edge detector GrabCut RANSAC Scale-invariant feature transform
Game play	AlphaGo AlphaGo Zero AlphaZero MuZero TD-Gammon
Related	Glossary of artificial intelligence List of algorithms List of algorithms for automated planning List of artificial intelligence journals List of machine learning algorithms List of quantum algorithms Lists of open-source artificial intelligence software Motion planning Outline of algorithms Outline of artificial intelligence Satplan TurboQuant AlphaDev AlphaEvolve AlphaTensor Algorithm engineering

v t e Data structures and algorithms
Data structures	Array Associative array Binary search tree Fenwick tree Graph Hash table Heap Linked list Queue Segment tree Stack String Tree Trie
Algorithms and algorithmic paradigms	Backtracking Binary search Breadth-first search Brute-force search Depth-first search Divide and conquer Dynamic programming Graph traversal Fold Greedy Hash function Minimax Online Randomized Recursion Root-finding Sorting Streaming Sweep line String-searching Topological sorting
List of data structures List of algorithms

Search

Search algorithms

Game-tree search

Optimization

Evolutionary and bio-inspired methods

Evolutionary computation

Bio-inspired methods

Reasoning and inference

Automated reasoning

Logic

Statistical inference

Planning and navigation

Pathfinding

Motion planning

Machine learning

Ensemble learning

Classification

Clustering

Association learning

Dimensionality reduction

Neural learning

Reinforcement learning

Deep learning

Other machine learning

Natural language processing

Computer vision

Algorithmic game play

See also

References