Modeling Physarum space exploration using memristors
- 1. Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100, Xanthi (Greece)
- 2. Centro de Investigación en Nanotecnologia y Materiales Avanzados, Department of Electrical Engineering, Pontificia Universidad Católica de Chile, 7820436, Santiago (Chile)
- 3. Unconventional Computing Centre, University of the West of England, Bristol, BS16 1QY (United Kingdom)
Description
Slime mold Physarum polycephalum optimizes its foraging behaviour by minimizing the distances between the sources of nutrients it spans. When two sources of nutrients are present, the slime mold connects the sources, with its protoplasmic tubes, along the shortest path. We present a two-dimensional mesh grid memristor based model as an approach to emulate Physarum's foraging strategy, which includes space exploration and reinforcement of the optimally formed interconnection network in the presence of multiple aliment sources. The proposed algorithmic approach utilizes memristors and LC contours and is tested in two of the most popular computational challenges for Physarum, namely maze and transportation networks. Furthermore, the presented model is enriched with the notion of noise presence, which positively contributes to a collective behavior and enables us to move from deterministic to robust results. Consequently, the corresponding simulation results manage to reproduce, in a much better qualitative way, the expected transportation networks. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1361-6463/aa614dAdditional details
Identifiers
Publishing Information
- Journal Title
- Journal of Physics. D, Applied Physics
- Journal Volume
- 50
- Journal Issue
- 17
- Journal Page Range
- [13 p.]
- ISSN
- 0022-3727
- CODEN
- JPAPBE
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49030218
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- DISTANCE; FORAGE; NOISE; PHYSARUM; SIMULATION; SPACE
- Descriptors DEC
- ANIMAL FEEDS; FOOD; FUNGI; PLANTS