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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

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Showing 151–175 of 261 papers

TitleStatusHype
HTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models—0
SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge—0
Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning—0
Scaling-up Generalized Planning as Heuristic Search with Landmarks—0
Searching for More Efficient Dynamic Programs—0
Search-Map-Search: A Frame Selection Paradigm for Action Recognition—0
Search-Space Characterization for Real-time Heuristic Search—0
Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster—0
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration—0
Solving 7x7 Killall-Go with Seki Database—0
Solving Mixed Model Workplace Time-dependent Assembly Line Balancing Problem with FSS Algorithm—0
Statistical Distance Based Deterministic Offspring Selection in SMC Methods—0
Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues—0
Symbolic Search for Optimal Planning with Expressive Extensions—0
Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices—0
Temporal Planning with Intermediate Conditions and Effects—0
Testing Deep Neural Networks—0
The Actor Search Tree Critic (ASTC) for Off-Policy POMDP Learning in Medical Decision Making—0
The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks—0
The Optimality of Satisficing Solutions—0
Theoretical Analysis of Heuristic Search Methods for Online POMDPs—0
The Partner Units Configuration Problem: Completing the Picture—0
The αμ Search Algorithm for the Game of Bridge—0
Topological Value Iteration Algorithms—0
Toward Efficient Task Assignment and Motion Planning for Large Scale Underwater Mission—0
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