A Counter Abstraction Technique for the Verification of Robot Swarms

Authors: Panagiotis Kouvaros, Alessio Lomuscio

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We present an implementation and discuss experimental results obtained for the alpha algorithm for robot swarms.
Researcher Affiliation Academia Panagiotis Kouvaros and Alessio Lomuscio Department of Computing, Imperial College London, UK
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper mentions MCMAS-P (MCMAS-P 2014) and provides a URL (http://vas.doc.ic.ac.uk/software/tools) which links to a general software tools page, not a direct source-code repository for the specific methodology described in the paper. There is no explicit statement of code release for the paper's methodology.
Open Datasets No The paper uses a simulated environment for the Alpha Algorithm case study, describing its parameters (sensor range 1, alpha parameter 2, 5x5 grid), but does not refer to a publicly available dataset in the conventional sense or provide access information for one.
Dataset Splits No The paper describes the setup for a simulated environment but does not specify any training, validation, or test dataset splits.
Hardware Specification Yes The simulation test took approximately 9 minutes and required 65 MB of memory on an Intel Core i7 machine clocked at 3.4 GHz, with 7.7 Gi B cache, running 64-bit Fedora 20, kernel 3.16.6.
Software Dependencies Yes We implemented the technique described in the previous section into a novel version of the experimental toolkit checker MCMAS-P (Kouvaros and Lomuscio 2013b; MCMAS-P 2014).
Experiment Setup Yes We chose an instance of alpha algorithm where we instantiated the sensor range to the value 1 and the alpha parameter to 2. We also fixed the environment to be a 5 5 square grid.