Informatics Journals | Jurnal Online Page 22

BAE*, and the independently developed DIBBS, are state-of-the-art bidirectional heuristic search algorithms that exploit heuristic consistency to effi...

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This position paper tackles a critical efficiency concern within state-of-the-art bidirectional heuristic search algorithms, particularly BAE* and DIB...

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André Schidler, Stefan Szeider

Extracting Problem Structure with LLMs for Optimized SAT Local Search

Informatics

Encoding combinatorial problems in terms of propositional satisfiability (SAT) enables utilization of highly efficient SAT solvers for combinatorial s...

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This position paper introduces a compelling and novel approach to enhance SAT local search through the specialized application of Large Language Model...

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Zhihui Xie, Xu Liu, Shuai Li

Multi-armed Bandit Algorithms for the Boolean Satisfiability Problem: A Survey

Informatics

This paper provides a survey of recent literature on the use of multi-armed bandit algorithms to solve the Boolean satisfiability problem (SAT), a wel...

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This survey paper addresses a highly relevant and impactful topic: the application of multi-armed bandit (MAB) algorithms to the Boolean Satisfiabilit...

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Jiaqi Tan, Yudong Luo, Jiaoyang Li, Hang Ma

Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities

Informatics

Multi-Agent Path Finding (MAPF) aims to arrange collision-free goal-reaching paths for a group of agents. Anytime MAPF solvers based on large neighbor...

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This paper presents a timely and critical reevaluation of Large Neighborhood Search (LNS) approaches for Multi-Agent Path Finding (MAPF). The authors...

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Dawson Tomasz, Richard Valenzano

Augmenting Exploration with Locally Greedy Probes

Informatics

Enhancing Greedy Best First Search (GBFS) with stochastic exploration will often greatly improve search performance. In this work, we show that one wa...

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This paper presents a compelling analysis of how stochastic exploration enhances Greedy Best First Search (GBFS), identifying that exploration often a...

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Takumi Shimoda, Alex Fukunaga

Decoupling Generation and Evaluation for Parallel Greedy Best-First Search

Informatics

In order to understand and control the search behavior of parallel search, recent work has proposed a class of constrained parallel greedy best-first...

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This paper tackles a pertinent challenge in the domain of parallel search, specifically concerning constrained parallel greedy best-first search algor...

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Daniel Koch, Stefan Funke

Guiding the Search for the Euclidean Shortest Path Problem

Informatics

We consider the problem of reducing the search space of algorithms which solve the Euclidean Shortest Path Problem by traversing a precomputed navigat...

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This work introduces a novel approach to optimize algorithms for the Euclidean Shortest Path Problem, specifically targeting those that navigate preco...

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Matej Husár, Jiří Švancara, Roman Barták

On Path Selection for Reduction-Based Solving of Multi-Agent Pathfinding Using Graph Pruning

Informatics

Multi-agent pathfinding is the task of navigating a set of mobile agents in a shared environment such that they avoid collisions. Finding an optimal s...

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This paper addresses a fundamental challenge in Multi-Agent Pathfinding (MAPF): the limitations of reduction-based algorithms when applied to larger p...

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Hasan Ferit Eniser, Songtuan Lin, Nicola Müller, Anastasia Isychev, Valentin Wüstholz, Isabel Valera, Jörg Hoffmann, Maria Christakis

Using Action-Policy Testing in RL to Reduce the Number of Bugs

Informatics

Reinforcement learning is becoming ever more prominent in solving combinatorial search problems, in particular ones where states are images. Prior wor...

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This paper presents a novel approach to improving the robustness of Reinforcement Learning policies by integrating action-policy testing directly into...

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The paper "Bi-Objective Search for the Traveling Salesman Problem with Time Windows and Vacant Penalties" investigates a significant extension to the...