Multiagent Simple Temporal Problem: The Arc-Consistency Approach
Authors: Shufeng Kong, Jae Hee Lee, Sanjiang Li
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical evaluations on diverse benchmark datasets also show that our AC-based algorithms for STP and Ma STP are significantly more efficient than existing approaches. |
| Researcher Affiliation | Academia | Shufeng Kong,1 Jae Hee Lee,1 Sanjiang Li1,2 1Centre for Quantum Software and Information, FEIT, University of Technology Sydney, Australia 2UTS-AMSS Joint Research Laboratory, AMSS, Chinese Academy of Sciences, China |
| Pseudocode | Yes | Algorithm 1: ACSTP (Page 3), Algorithm 2: Dis ACSTP (Page 4) |
| Open Source Code | Yes | The source code for our evaluation can be found in https://github.com/sharingcodes/Ma STN |
| Open Datasets | Yes | We selected instances from the benchmark datasets of STNs used in (Planken, de Weerdt, and van der Krogt 2012) for evaluations. ... We also considered graphs that are based on the road network of New York City (New York). ... We selected instances from the benchmark datasets of Ma STNs used in (Boerkoel and Durfee 2013) for evaluations. |
| Dataset Splits | No | The paper describes the datasets used for evaluation but does not specify how these datasets were split into training, validation, and test sets. It focuses on evaluating the algorithms on problem instances rather than training a machine learning model. |
| Hardware Specification | Yes | Our experiments were implemented in Python 3.6 and carried out on a computer with an Intel Core i5 processor with a 2.9 GHz frequency per CPU, 8 GB memory |
| Software Dependencies | No | The paper only mentions "Python 3.6" as an implementation detail. It does not list any specific versioned libraries or solvers, which are required for a reproducible description of ancillary software. |
| Experiment Setup | Yes | All experiments for distributed algorithms used an asynchronous simulator in which agents are simulated by processes which communicate only through message passing and default communication latency is assumed to be zero. |