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..
Efficient Temporal Planning Using Metastates
Authors: Amanda Coles, Andrew Coles, J. Christopher Beck7554-7561
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our evaluation shows that this approach, implemented in OPTIC and compared to existing state-of-the-art memoisation techniques, improves performance across a range of temporal domains. We empirically evaluate our approach on temporal planning domains and our results show a significant improvement in performance over the state-of-the-art in memoisation for temporal planning. |
| Researcher Affiliation | Academia | Amanda Coles, Andrew Coles, J. Christopher Beck *Department of Informatics, King s College London, UK. Department of Mechanical & Industrial Engineering, University of Toronto, Canada. email: {amanda,andrew}.EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Memoise, Algorithm 2: Add Member To Meta State, Algorithm 3: Search, Algorithm 4: Find Another Member |
| Open Source Code | No | The paper does not provide any explicit statements about releasing the source code or links to a code repository for the methodology described. |
| Open Datasets | Yes | For evaluation domains, we take International Planning Competition benchmarks and temporally interesting domains from the literature. Cafe and Driverlog Shift (Coles et al. 2009); P2P (Huang et al. 2009); TMS and Turn and Open (IPC2011); the compiled timewindows/deadlines variants of Pipes No-Tankage, Satellite and UMTS (IPC2004) and 5 other IPC domains Rovers (2002); Pipes Tankage (2004); Transport, Elevators and Openstacks (2008). |
| Dataset Splits | No | The paper mentions using International Planning Competition benchmarks but does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts). |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions that the approach is implemented in 'OPTIC' and uses 'PDDL2.1', but it does not specify version numbers for these or any other software dependencies. |
| Experiment Setup | Yes | In both cases we use WA* search (with W=5); and a temporal RPG heuristic, as in OPTIC. |