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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 151–200 of 261 papers

TitleStatusHype
Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems—0
Get Your Workload in Order: Game Theoretic Prioritization of Database Auditing—0
Goal-directed Generation of Discrete Structures with Conditional Generative Models—0
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network—0
Grid-based angle-constrained path planning—0
Hardware Distortion Modeling for Panel Selection in Large Intelligent Surfaces—0
Heuristic Search as Evidential Reasoning—0
Heuristic Search for Multi-Objective Probabilistic Planning—0
Heuristic Search for Path Finding with Refuelling—0
Heuristic Search For Physics-Based Problems: Angry Birds in PDDL+—0
Heuristic Search for Rank Aggregation with Application to Label Ranking—0
Heuristic Search for Structural Constraints in Data Association—0
Heuristic Search Planning with Deep Neural Networks using Imitation, Attention and Curriculum Learning—0
Heuristics for vehicle routing problems: Sequence or set optimization?—0
Homotopy based algorithms for _0-regularized least-squares—0
HSVI-based Online Minimax Strategies for Partially Observable Stochastic Games with Neural Perception Mechanisms—0
HSVI can solve zero-sum Partially Observable Stochastic Games—0
HSVI for zs-POSGs using Concavity, Convexity and Lipschitz Properties—0
Ideal Reformulation of Belief Networks—0
Implicit Abstraction Heuristics—0
Improved Safe Real-time Heuristic Search—0
Improving Learnt Local MAPF Policies with Heuristic Search—0
Inconsistency and Accuracy of Heuristics with A* Search—0
Induction, of and by Probability—0
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters—0
Inductive Bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters—0
Influence-Optimistic Local Values for Multiagent Planning --- Extended Version—0
Interactive Ant Colony Optimisation (iACO) for Early Lifecycle Software Design—0
Iterative Budgeted Exponential Search—0
LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner—0
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data—0
Learning in Real-Time Search: A Unifying Framework—0
Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)—0
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising—0
Learning to Solve Soft-Constrained Vehicle Routing Problems with Lagrangian Relaxation—0
Local Optima Networks: A New Model of Combinatorial Fitness Landscapes—0
Unlocking the Secrets of Software Configuration Landscapes-Ruggedness, Accessibility, Escapability, and Transferability—0
Mean-based Heuristic Search for Real-Time Planning—0
MEMA Runtime Framework: Minimizing External Memory Accesses for TinyML on Microcontrollers—0
RBF-HS: Recursive Best-First Hitting Set Search—0
MeshA*: Efficient Path Planing With Motion Primitives—0
Microgrid Planner: A Distributed Energy Resource Sizing Method—0
Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results—0
Movable-Element STARS-Assisted Near-Field Wideband Communications—0
Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering—0
Multi-objective Evolution of Heuristic Using Large Language Model—0
Multi-Resolution A*—0
Multi-Robot Path Planning Combining Heuristics and Multi-Agent Reinforcement Learning—0
NaviAgent: Bilevel Planning on Tool Dependency Graphs for Function Calling—0
Neural Machine Translation with Gumbel-Greedy Decoding—0
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