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..
Planning with Numeric Timed Initial Fluents
Authors: Chiara Piacentini, Maria Fox, Derek Long
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this paper we present an extension of the planner POPF2 (POPF-TIF) to handle problems with numeric Timed Initial Fluents. We propose and evaluate two contributions: the ο¬rst is based on improvements of the heuristic evaluation, while the second considers alternative search algorithms based on a mixture of Enforced Hill Climbing and Best First Search. 4 Experimental Evaluation We now present results of the planner POPF-TIF with the following domains (30 problems each domain): |
| Researcher Affiliation | Academia | Chiara Piacentini, Maria Fox, Derek Long Informatics Department King s College London London, UK email: EMAIL |
| Pseudocode | No | The paper describes algorithms but does not provide structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statement or link indicating the availability of open-source code for the methodology described. |
| Open Datasets | Yes | Unit Commitment Problem (UCP); Rover domain: a variant of the numeric rover domain in which the rover is equipped with a solar panel that gives energy to the rover according to the exposure to the sun. Temperature domain: a PDDL version of the problem presented in (Ono, Graybill, and Williams 2012), where the objective is to maintain the temperature of a smart home within the user s preferences. Skier domain: |
| Dataset Splits | No | The paper mentions '30 problems each domain' but does not provide specific dataset split information (e.g., percentages, sample counts, or explicit validation splits) needed for reproduction. |
| Hardware Specification | Yes | All tests used a 3.4 GHz Intel Core i7-2600 machine, limited to 30 minutes and 4 GB of memory. |
| Software Dependencies | No | The paper mentions planners like POPF2 and UPMurphi but does not provide specific version numbers for these or any other software dependencies. |
| Experiment Setup | Yes | For each search strategy we use heuristic evaluations with a different number of lookaheads, from 0 to 10, where 0 indicates the standard heuristic evaluation. |