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..
Optimising Partial-Order Plans Via Action Reinstantiation
Authors: Max Waters, Lin Padgham, Sebastian Sardina
IJCAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We also propose a MAXSAT-based technique for increasing plan flexibility and provide a thorough experimental evaluation that suggests that there are benefits in action reinstantiation. |
| Researcher Affiliation | Academia | Max Waters , Lin Padgham and Sebastian Sardina RMIT University, Melbourne, Victoria 3000, Australia EMAIL |
| Pseudocode | No | The paper describes encoding methods using formulas (e.g., Formulae 1-17) but does not present them in a structured pseudocode or algorithm block. |
| Open Source Code | Yes | Implementation is available at bitbucket.org/max waters/mrr |
| Open Datasets | Yes | Test cases (i.e., input plans) were generated by giving all first-order IPC STRIPS planning instances to three planners. |
| Dataset Splits | No | The paper generates 'test cases' (input plans) from IPC STRIPS planning instances and evaluates optimization techniques, but it does not describe specific training, validation, or test splits for a dataset in the context of model training. |
| Hardware Specification | Yes | Plan generation and encoding/optimisation were both limited to 8GB and 30m at 2.60GHz. |
| Software Dependencies | No | The paper mentions 'Loandra MAXSAT solver' and 'Max Pre [Korhonen et al., 2017]' but does not provide specific version numbers for these software components. |
| Experiment Setup | Yes | Test cases (i.e., input plans) were generated by giving all first-order IPC STRIPS planning instances to three planners. To ensure a variety of plans, three planners of distinct types were used: the novelty-driven best-first search planner Dual BFWS [Lipovetzky and Geffner, 2017], the heuristic forward-search planner LAMA [Richter and Westphal, 2010] and the SAT planner Madagascar [Rintanen, 2010]. Each (unique) plan was encoded with each encoding2, and the resulting MAXSAT instances were preprocessed with Max Pre [Korhonen et al., 2017] and given to the Loandra MAXSAT solver. Plan generation and encoding/optimisation were both limited to 8GB and 30m at 2.60GHz. |