Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..

Path Planning with CPD Heuristics

Authors: Massimo Bono, Alfonso E. Gerevini, Daniel D. Harabor, Peter J. Stuckey

IJCAI 2019 | Venue PDF | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We evaluate CPD-Search in two online settings: optimal search and anytime search. In both experiments we use grid benchmarks drawn from Sturtevant s well known repository at http://movingai.com.
Researcher Affiliation Academia 1Dipartimento di Ingegneria dell Informazione, Universit a degli Studi di Brescia, Brescia, Italy 2Faculty of Information Technology, Monash University, Melbourne, Australia
Pseudocode Yes Algorithm 1: CPD-Search(w, w , s, t, ϵ): Variant of Weighted A* with a CPD heuristic. Algorithm 2: w CPD(s,t): Retrieving the original (using w) and new (using w ) cost of the shortest path (according to w) for an (s, t) pair.
Open Source Code Yes All codes are in C++ and available from https://bitbucket.org/koldar/astar-early-stop/.
Open Datasets Yes In both experiments we use grid benchmarks drawn from Sturtevant s well known repository at http://movingai.com.
Dataset Splits No The paper uses grid benchmarks with various instances (start-target pairs) for evaluation but does not specify a training, validation, or test dataset split in the typical machine learning sense.
Hardware Specification Yes Our test machine is a i78700 machine with 16GB memory.
Software Dependencies No The paper states 'All codes are in C++', but does not provide specific version numbers for any libraries, frameworks, or other software dependencies.
Experiment Setup Yes We use a radius r = 15 and a weight multiplication of w'(e) = w(e) (3e^(-x^2/45) + 1) where x is the number of hops from node n to edge e. We implement ALT with different numbers of landmark nodes, up to diminishing returns: 6, 12 and 18.