Automated Verification of Social Laws for Continuous Time Multi-Robot Systems
Authors: Ronen Nir, Erez Karpas7683-7690
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we provide an empirical evaluation which demonstrates our compilation on a real multi-robot system as well as on several PDDL 2.1 domains. In order to empirically evaluate our compilation, we implemented it in Python. We evaluated our compilation on one real world multi robot system and on 5 virtual PDDL domains |
| Researcher Affiliation | Academia | Ronen Nir, Erez Karpas Technion Israel Institute of Technology Haifa, Israel ronen.nir@outlook.com, karpase@technion.ac.il |
| Pseudocode | No | The paper provides formal definitions for its compilation components (Facts, Initial State, Goal State, Actions) using structured descriptions with conditions and effects, but these are not explicitly labeled or formatted as "Pseudocode" or "Algorithm" blocks for a procedural process. |
| Open Source Code | No | The paper states "These new domains are available at https://tinyurl.com/y8cbgqbn" which points to PDDL domains, not the Python compilation code. It does not provide concrete access to the source code for the compilation methodology. |
| Open Datasets | Yes | To conclude our empirical evaluation, and show the scalability of our compilation, we also used IPC Benchmark domains. We adapted each domain to our multi-agent setting by deciding who the agents were and assigning goal facts (from the original goal) to each agent. We used 3 domains: DRIVERLOG (IPC 2002), ZENOTRAVEL (IPC 2002), and FLOORTILE (IPC 2008), and formulated a social law for each of them. |
| Dataset Splits | No | The paper discusses adapting planning domains and using different instances of those domains. It does not provide specific training/validation/test dataset splits in the machine learning context. |
| Hardware Specification | Yes | We used a single Intel i7-7700K core on a computer with 32GB of RAM, and with a time limit of 30 minutes. |
| Software Dependencies | No | The paper mentions "implemented it in Python" and "used the OPTIC planner (Benton, Coles, and Coles 2012) with the CLP solver". However, it does not provide specific version numbers for Python or the OPTIC planner itself, nor for any other ancillary libraries or software used for implementation or experimentation. |
| Experiment Setup | Yes | We used a single Intel i7-7700K core on a computer with 32GB of RAM, and with a time limit of 30 minutes. marking the fact that the cup is on the table as a wait-for condition also results in a failure. we formulated a social law which assigns each tile to a speciļ¬c robot. |