FOND Planning with Explicit Fairness Assumptions
Authors: Ivan D. Rodriguez, Blai Bonet, Sebastian Sardina, Hector Geffner
JAIR 2022 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | A sound and complete FOND+ planner is implemented by reducing FOND+ planning to answer set programs, and its performance is evaluated in comparison with FOND and QNP planners, and LTL synthesis tools. |
| Researcher Affiliation | Academia | Ivan D. Rodriguez EMAIL Blai Bonet EMAIL Universitat Pompeu Fabra, Barcelona, Spain Sebastian Sardina EMAIL RMIT University, Melbourne, Australia Hector Geffner EMAIL Universitat Pompeu Fabra, Barcelona, Spain Instituci o Catalana de Recerca i Estudis Avanc ats (ICREA), Barcelona, Spain Link oping University, Link oping, Sweden |
| Pseudocode | Yes | The code for the back-end of the ASP-based FOND+ planner is shown in Figure 2. The frontend of the planner, not shown, parses an input problem Pc = P,C and builds a flat representation of Pc in terms of a number of ground atoms that are shown in capitalized predicates in the figure. The code in the figure and the facts representing the problem are fed to the ASP solver CLINGO, which either returns a (stable) model for the program or reports that no such model exists. |
| Open Source Code | Yes | Planner and problems available at https://github.com/idrave/fond-asp |
| Open Datasets | Yes | The pure (strong and strong-cyclic) FOND problems are those in the FOND-SAT distribution, the QNPs are those by Bonet and Geffner (2020), and two new families of instances that grow in size with a parameter. |
| Dataset Splits | No | The paper analyzes results on various problem families (FOND problems, QNPs, and FOND+ problems) and mentions problem sizes (e.g., 'n' for QNP families) but does not specify any training, testing, or validation dataset splits. |
| Hardware Specification | No | The paper evaluates performance in terms of time and memory but does not provide specific hardware details such as CPU, GPU models, or memory specifications used for the experiments. |
| Software Dependencies | No | The paper mentions several software tools like CLINGO ASP solver (Gebser, Kaminski, Kaufmann, & Schaub, 2019), FOND-SAT (Geffner & Geffner, 2018), PRP (Muise et al., 2012), and STRIX (Luttenberger, Meyer, & Sickert, 2020), but it does not provide specific version numbers for these software components. |
| Experiment Setup | Yes | The code for the back-end of the ASP-based FOND+ planner is shown in Figure 2. The frontend of the planner, not shown, parses an input problem Pc = P,C and builds a flat representation of Pc in terms of a number of ground atoms that are shown in capitalized predicates in the figure. The code in the figure and the facts representing the problem are fed to the ASP solver CLINGO, which either returns a (stable) model for the program or reports that no such model exists. |