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Heuristic Search

Heuristic Search is a problem-solving method that uses practical rules or "guides" (heuristics) to find solutions more quickly than exhaustive search, by focusing on the most promising paths first.

Papers

Showing 2650 of 261 papers

TitleStatusHype
Learning Heuristic Search via ImitationCode1
Heuristic Domain AdaptationCode1
ASNets: Deep Learning for Generalised PlanningCode0
A More General Theory of Diagnosis from First PrinciplesCode0
LLM-Virus: Evolutionary Jailbreak Attack on Large Language ModelsCode0
ARMS: Automated rules management system for fraud detectionCode0
MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment DesignCode0
Learning Heuristic Selection with Dynamic Algorithm ConfigurationCode0
A Novel Point-based Algorithm for Multi-agent Control Using the Common Information ApproachCode0
Hybrid Planning for Dynamic Multimodal Stochastic Shortest PathsCode0
Learning Loop Invariants for Program VerificationCode0
On Parallel External-Memory Bidirectional SearchCode0
Front-to-End Bidirectional Heuristic Search with Near-Optimal Node ExpansionsCode0
An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the EdgeCode0
Generalized Planning as Heuristic Search: A new planning search-space that leverages pointers over objectsCode0
Factored World Models for Zero-Shot Generalization in Robotic ManipulationCode0
BeamAttack: Generating High-quality Textual Adversarial Examples through Beam Search and Mixed Semantic SpacesCode0
Fanoos: Multi-Resolution, Multi-Strength, Interactive Explanations for Learned SystemsCode0
Finding Optimal Diverse Feature Sets with Alternative Feature SelectionCode0
Evolving Deep Convolutional Neural Networks for Image ClassificationCode0
Fast threshold optimization for multi-label audio tagging using Surrogate gradient learningCode0
DeepType: Multilingual Entity Linking by Neural Type System EvolutionCode0
Deliberative and Conceptual Inference in Service RobotsCode0
Crafting a Pogo Stick in Minecraft with Heuristic Search (Extended Abstract)Code0
Discovering Reliable Correlations in Categorical DataCode0
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