Glossary
Beam Search Algorithm
Fundamentals
Adversarial Machine LearningAI AgentsAI and EducationAI and MedicineAI AssistantsAI HardwareAI Voice TransferApproximate Dynamic ProgrammingBackpropagationBayesian Machine LearningCurse of DimensionalityData LabelingDeep LearningDeep Reinforcement LearningDimensionality ReductionF1 Score in Machine LearningFeedforward Neural NetworkFine Tuning in Deep LearningGated Recurrent UnitGenerative AILarge Language Model (LLM)Machine LearningMultimodal LearningNatural Language Generation (NLG)Natural Language Processing (NLP)Natural Language Understanding (NLU)Precision and RecallTransformersZero-shot Classification Models
Models
AlphaGo ZeroBERTChatGPTChess botsDall-EDiffusion ModelsDistilBERTGoogle's BardHidden Markov Models (HMMs)Inference EngineLarge Language Model (LLM)Llama 2LLM CollectionMidjourney (Image Generation)MistralOpenAI WhisperPerceptronProbabilistic Models in Machine LearningRoBERTaRule-Based AISpeech-to-text modelsText-to-Speech ModelsXLNet
Techniques
Activation FunctionsBatch Gradient DescentBeam Search AlgorithmBenchmarkingClassificationCURE AlgorithmExpectation MaximizationFlajolet-Martin AlgorithmGaussian ProcessesGenerative Adversarial Networks (GANs)Gradient Boosting Machines (GBMs)Gradient ClippingGradient ScalingGroundingHyperparametersk-ShinglesLatent Dirichlet Allocation (LDA)Mixture of ExpertsMultimodal AIOnline Gradient DescentOverfitting and UnderfittingPrompt ChainingPrompt EngineeringRetrieval-Augmented Generation (RAG)RLHFSentiment AnalysisSequence ModelingSemantic KernelTokenizationWinnow AlgorithmWord Embeddings
Last updated on January 30, 202410 min read
Beam Search Algorithm

The Beam Search algorithm is a powerful tool in the arsenal of heuristic search strategies that offers a pragmatic balance between the exhaustive rigor of breadth-first search and the nimble agility of greedy algorithms.

The Beam Search algorithm is a powerful tool in the arsenal of heuristic search strategies that offers a pragmatic balance between the exhaustive rigor of breadth-first search and the nimble agility of greedy algorithms. By focusing on the most promising paths and pruning away the chaff, Beam Search stands out as a beacon of hope for those wrestling with vast search spaces.

Section 1: What is the Beam Search Algorithm?

The Beam Search algorithm is a heuristic search algorithm that stands out for its unique approach to exploring a graph. Rather than expanding all nodes, it selects and expands the most promising node within a limited set—much like casting a focused beam of light into a room and only observing objects within that beam. This method is an evolution of the breadth-first search, but with a twist: it operates under a limited memory capacity. Here's how it works:

The Beam Search is a variation of A* that places a limit on the size of the OPEN set. If you’re unfamiliar with A*, don’t worry. We can illustrate Beam Search rather simply using graphs. The pseudocode is written in the image below.