Sorting Sequential Portfolios in Automated Planning
Authors: Sergio Núñez, Daniel Borrajo, Carlos Linares López
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically show that our greedy approach produces near-optimal solutions very quickly and that it generalizes much better than an optimal solution wrt to a specific training set which has been observed to suffer from overfitting. 3. An extensive evaluation is performed with the algorithms introduced here, a random ordering algorithm and others from the literature with data from the last three IPCs. |
| Researcher Affiliation | Academia | Sergio N u nez and Daniel Borrajo and Carlos Linares L opez Computer Science Department Universidad Carlos III de Madrid (Spain) {sergio.nunez,daniel.borrajo,carlos.linares}@uc3m.es |
| Pseudocode | No | The paper describes the algorithms (DFBn B and SLOPE) in prose, detailing their steps, but does not present them as structured pseudocode or in a clearly labeled algorithm block. |
| Open Source Code | No | The paper does not provide any links to its own source code for the described methodologies, nor does it explicitly state that the code is publicly available. |
| Open Datasets | Yes | An extensive evaluation is performed with the algorithms introduced here, a random ordering algorithm and others from the literature with data from the last three IPCs. ... http://ipc.icaps-conference.org |
| Dataset Splits | No | The paper describes training and test sets (e.g., 'training set' from IPC 2008, 'test set' from IPC 2011) but does not mention a separate validation set. |
| Hardware Specification | Yes | We have used an Intel Xeon 2.93 GHZ quad core processor with 8 GB of RAM. |
| Software Dependencies | No | The paper mentions 'CPLEX license' and refers to general techniques like 'Mixed-integer programming technique (MIP)' but does not provide specific version numbers for any software dependencies or libraries. |
| Experiment Setup | Yes | The time limit T used is 1800 seconds. ... The size of the candidate and component planners sets are defined in the ranges [8, 38] and [3, 14] respectively. |