A Graph-Transformational Approach to Swarm Computation
In this paper, we propose a graph-transformational approach to swarm computation that is flexible enough to cover various existing notions of swarms and swarm computation, and it provides a mathematical basis for the analysis of swarms with respect to their correct behavior and efficiency. A graph t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/4/453 |
| _version_ | 1797537979204370432 |
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| author | Larbi Abdenebaoui Hans-Jörg Kreowski Sabine Kuske |
| author_facet | Larbi Abdenebaoui Hans-Jörg Kreowski Sabine Kuske |
| author_sort | Larbi Abdenebaoui |
| collection | DOAJ |
| description | In this paper, we propose a graph-transformational approach to swarm computation that is flexible enough to cover various existing notions of swarms and swarm computation, and it provides a mathematical basis for the analysis of swarms with respect to their correct behavior and efficiency. A graph transformational swarm consists of members of some kinds. They are modeled by graph transformation units providing rules and control conditions to specify the capability of members and kinds. The swarm members act on an environment—represented by a graph—by applying their rules in parallel. Moreover, a swarm has a cooperation condition to coordinate the simultaneous actions of the swarm members and two graph class expressions to specify the initial environments on one hand and to fix the goal on the other hand. Semantically, a swarm runs from an initial environment to one that fulfills the goal by a sequence of simultaneous actions of all its members. As main results, we show that cellular automata and particle swarms can be simulated by graph-transformational swarms. Moreover, we give an illustrative example of a simple ant colony the ants of which forage for food choosing their tracks randomly based on pheromone trails. |
| first_indexed | 2024-03-10T12:24:55Z |
| format | Article |
| id | doaj.art-39126bd621fe4e459cfa3e4b4cbc16ef |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T12:24:55Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-39126bd621fe4e459cfa3e4b4cbc16ef2023-11-21T15:08:48ZengMDPI AGEntropy1099-43002021-04-0123445310.3390/e23040453A Graph-Transformational Approach to Swarm ComputationLarbi Abdenebaoui0Hans-Jörg Kreowski1Sabine Kuske2OFFIS—Institute for Information Technology, Escherweg 2, 26122 Oldenburg, GermanyDepartment of Computer Science, University of Bremen, P.O. Box 330440, D-28334 Bremen, GermanyDepartment of Computer Science, University of Bremen, P.O. Box 330440, D-28334 Bremen, GermanyIn this paper, we propose a graph-transformational approach to swarm computation that is flexible enough to cover various existing notions of swarms and swarm computation, and it provides a mathematical basis for the analysis of swarms with respect to their correct behavior and efficiency. A graph transformational swarm consists of members of some kinds. They are modeled by graph transformation units providing rules and control conditions to specify the capability of members and kinds. The swarm members act on an environment—represented by a graph—by applying their rules in parallel. Moreover, a swarm has a cooperation condition to coordinate the simultaneous actions of the swarm members and two graph class expressions to specify the initial environments on one hand and to fix the goal on the other hand. Semantically, a swarm runs from an initial environment to one that fulfills the goal by a sequence of simultaneous actions of all its members. As main results, we show that cellular automata and particle swarms can be simulated by graph-transformational swarms. Moreover, we give an illustrative example of a simple ant colony the ants of which forage for food choosing their tracks randomly based on pheromone trails.https://www.mdpi.com/1099-4300/23/4/453swarm computationgraph transformationcellular automataparticle swarms |
| spellingShingle | Larbi Abdenebaoui Hans-Jörg Kreowski Sabine Kuske A Graph-Transformational Approach to Swarm Computation Entropy swarm computation graph transformation cellular automata particle swarms |
| title | A Graph-Transformational Approach to Swarm Computation |
| title_full | A Graph-Transformational Approach to Swarm Computation |
| title_fullStr | A Graph-Transformational Approach to Swarm Computation |
| title_full_unstemmed | A Graph-Transformational Approach to Swarm Computation |
| title_short | A Graph-Transformational Approach to Swarm Computation |
| title_sort | graph transformational approach to swarm computation |
| topic | swarm computation graph transformation cellular automata particle swarms |
| url | https://www.mdpi.com/1099-4300/23/4/453 |
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