Heuristic Planning for PDDL+ Domains
Authors: Wiktor Piotrowski, Maria Fox, Derek Long, Daniele Magazzeni, Fabio Mercorio
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Section 5 describes the experimental evaluation. In this section we evaluate the performance of Di No on PDDL+ benchmark domains. |
| Researcher Affiliation | Academia | Wiktor Piotrowski,1 Maria Fox,1 Derek Long,1 Daniele Magazzeni,1 Fabio Mercorio2 1Department of Informatics, King s College London, United Kingdom 2Department of Statistics and Quantitative Methods, CRISP Research Centre, University of Milan-Bicocca, Italy |
| Pseudocode | Yes | Algorithm 4.1: Building the SRPG |
| Open Source Code | No | The paper provides a URL for 'more information' (kcl-planning.github.io/Di No) but does not explicitly state that the source code for the methodology described in the paper is available there. |
| Open Datasets | Yes | For our experimental evaluation, we consider two benchmark domains: Generator and Car. In addition, we also consider two more domains that highlight specific aspects of Di No: Solar Rover that shows how Di No handles TILs, and Powered Descent that further tests its non-linear capabilities. (Generator. This domain [Howey and Long, 2003] is well-known across the planning community... The Car domain [Fox and Long, 2006]...) |
| Dataset Splits | No | The paper evaluates performance on different problem instances within benchmark domains but does not describe explicit training, validation, or testing dataset splits in terms of percentages, sample counts, or specific predefined partitions. |
| Hardware Specification | Yes | For a fair comparison, all results were achieved by running the competitor planners on a machine with an 8-core Intel Core i7 CPU, 8GB RAM and Ubuntu 14.04 operating system. |
| Software Dependencies | No | The paper mentions 'Ubuntu 14.04 operating system' but does not specify version numbers for other key software components, libraries, or solvers used in the experiments. |
| Experiment Setup | Yes | Note that to achieve the results a discretisation of t = 1.0 was chosen, except non-linear Generator where some problems required refinement to t = 0.5. (...) In both variants of the domain, time horizon was set to T = 1000, that is the duration for which the generator is requested to run. (...) For both variants of the domain, the time horizon is set depending on the time point at which the sunexposure TIL is triggered (as defined in the problems). (...) The SRPG time horizon was set to T = 20 for the first 3 problems and T = 40 for the remaining problem instances based on the equations in the domain. |