LAPSE:2023.24822
Published Article
LAPSE:2023.24822
On Numerical 2D P Colonies Modelling the Grey Wolf Optimization Algorithm
Daniel Valenta, Miroslav Langer
March 28, 2023
The 2D P colonies is a version of the P colonies with a two-dimensional environment designed for observing the behavior of the community of very simple agents living in the shared environment. Each agent is equipped with a set of programs consisting of a small number of simple rules. These programs allow the agent to act and move in the environment. The 2D P colonies have been shown to be suitable for the simulations of various (not only) multi-agent systems, and natural phenomena, like flash floods. The Grey wolf algorithm is the optimization-based algorithm inspired by social dynamics found in packs of grey wolves and by their ability to create hierarchies, in which every member has a clearly defined role, dynamically. In our previous papers, we extended the 2D P colony by the universal communication device, the blackboard. The blackboard allows for the agents to share various information, e.g., their position or the information about their surroundings. In this paper, we follow our previous research on the numerical 2D P colony with the blackboard. We present the computer simulator of the numerical 2D P colony with the blackboard and the results of the computer simulation, and we compare these results with the original algorithm.
Keywords
2D P colonies, Algorithms, blackboard, data structures, Grey wolf optimization algorithm, P systems, Simulation
Suggested Citation
Valenta D, Langer M. On Numerical 2D P Colonies Modelling the Grey Wolf Optimization Algorithm. (2023). LAPSE:2023.24822
Author Affiliations
Valenta D: Institute of Computer Science, Silesian University in Opava, 746 01 Opava, Czech Republic
Langer M: Institute of Computer Science, Silesian University in Opava, 746 01 Opava, Czech Republic; Research Institute of the IT4Innovations Centre of Excellence, Silesian University in Opava, 746 01 Opava, Czech Republic [ORCID]
Journal Name
Processes
Volume
9
Issue
2
First Page
330
Year
2021
Publication Date
2021-02-11
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9020330, Publication Type: Journal Article
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LAPSE:2023.24822
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doi:10.3390/pr9020330
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