Splitting a Logic Program Revisited
Authors: Jianmin Ji, Hai Wan, Ziwei Huo, Zhenfeng Yuan
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show that for some typical programs the splitting process is efficient, which implies some potential applications. Second, we use the concept of splitting to investigate the program simplification problem, i.e., how to simplify a program by a set of atoms that are satisfied by every answer set of the program. We show that this problem can be regarded as a splitting problem, which results a new approach to simplify a program. Table 1 contains the running times for these programs split in such way. |
| Researcher Affiliation | Academia | Jianmin Ji School of Computer Science and Technology University of Science and Technology of China Hefei 230027, China jianmin@ustc.edu.cn Hai Wan, Ziwei Huo, Zhenfeng Yuan School of Software Sun Yat-sen University Guangzhou 510006, China wanhai@mail.sysu.edu.cn |
| Pseudocode | Yes | Algorithm 1: dsl U(P, X) |
| Open Source Code | Yes | The usefulness of the result is illustrated through two aspects. First, we discuss some computational complexity issues related to the splitting method. We show that for some typical programs the splitting process is efficient, which implies some potential applications. [...] http://ss.sysu.edu.cn/%7ewh/splitting.html |
| Open Datasets | No | The paper mentions generating graphs for the Hamiltonian Circuit problem: 'For each 2-N entry in the table, we randomly create 10 different such graphs'. This indicates that the data was synthetically generated or modeled, not sourced from a publicly available dataset with specific access information. |
| Dataset Splits | No | The paper does not specify training, validation, or test dataset splits. The evaluation is based on computing answer sets for generated logic programs rather than training models on data splits. |
| Hardware Specification | Yes | Our experiments were done on a Linux machine with AMD A10-5800K (3.8GHz) CPU and 3.3GB RAM. |
| Software Dependencies | Yes | The numbers under whole refer to the running times (in seconds) of clasp (version 3.1.0 (Gebser et al. 2007)) for the whole programs. |
| Experiment Setup | No | The paper describes the generation of graphs for the Hamiltonian Circuit problem and how they are split for evaluation. However, it does not provide specific experimental setup details such as hyperparameters, optimization settings, or other typical training configurations commonly found in machine learning papers. |