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Modelling the Adaptability of Biological Systems
by Eugene Ch'ng
The Open Journal of Cybernetics and Systemics
There are millions of species of organisms in estimation today, each possessing different preferences or tolerance... more
There are millions of species of organisms in estimation today, each possessing different preferences or tolerance towards a multitude of factors; these factors include mainly competition between species and environmental conditions. From a computer modelling point of view, these biological systems could be difficult to implement. However, if a unified formula could be found to measure all of the factors against the preferences of each life form, its potentials for modelling open systems that require multiple external input variables could be significant. This article explores a formula and variations of it as applied first to measure sessile systems – vegetation, which requires multiple variables for determining its fitness, and then to a pilot study exploring its use for dynamic vagile systems. Experiments suggest that using the formula and variations of it on vegetation communities yielded distribution patterns similar to those in natural landscapes. Experiments using the formula in the pilot study showed characteristics of emergent behaviours as each dynamic system seeks its own ecological niche. The findings provided evidence that the formula could be extended for modelling a wide variety
of open biological systems.
Spatially Realistic Positioning of Plants for Virtual Environments: Simple Biotic and Abiotic Interaction for Populating Terrains
by Eugene Ch'ng
Published IEEE Computer Graphics and Applications (Final Unformatted Manuscript shown)
Creating natural forest landscapes for virtual environments require some basic knowledge of botany and ecology,... more Creating natural forest landscapes for virtual environments require some basic knowledge of botany and ecology, without which the terrain may appear synthetic. While tools such as scene editors have made a designer’s job easier, manually creating a natural-looking landscape is time consuming and, depending on the knowledge the artist possesses, often do not follow the principles of ecology and spatially viable plant positioning. This research attempts to study how lessons from ecological modelling can be adopted for growing vegetation as ground cover for outdoor scenes of virtual worlds. The algorithms presented attempt to simulate ecologically and spatially realistic placement of plants, from which the XML-based position data can be used for populating other 2D and 3D virtual worlds. The simulation results show the potentials of such a venture in future more complex developments, such as real-time plant growth and state changes in virtual environments.
A Behavioural Agent Model for Synthesising Vegetation Distribution Patterns on 3D Terrains
by Eugene Ch'ng
Applied AI.
Vegetations, similar to other organisms, persist on terrains based on niches of their abiotic and biotic environments.... more Vegetations, similar to other organisms, persist on terrains based on niches of their abiotic and biotic environments. Agent-based models of vegetation have demonstrated that, via the process of macro self-organisation, are capable of forming forests and undergrowth by means of their behaviour and the resources available in the ecosystem. In order to more accurately synthesise their collective behaviour, a set of rules encompassing basic vegetation behaviour were defined to enable realistic patterns to be formed locally via interaction and extra-locally via emergence in accord with their preferences in various controlled environments. Furthermore, the use of botanical parameters fine-tuned and regulated via simple rules could, in the near future, become a potential model for determining large-scale spatial and temporal distribution of dominant vegetation species, enhancing traditional methods and visualisation in studies related to forest dynamics and research in landscape reconstruction.
AN EFFICIENT SEGMENTATION ALGORITHM FOR ENTITY INTERACTION
by Eugene Ch'ng
artificial life, entity interaction, individual-based model, optimisation algorithms,
segmentation
The inventorying of biological diversity and studies in biocomplexity require the management of large electronic... more
The inventorying of biological diversity and studies in biocomplexity require the management of large electronic datasets of organisms. While species inventory has adopted
structured electronic databases for some time, the computer modelling of the functional interactions between biological entities at all levels of life is still in the stage of development. One of the challenges for this type of modelling is the biotic interactions that occur between large datasets of entities represented as computer algorithms. In real-time simulation that models the biotic interactions of large population datasets, the use of computational processing time could be extensive. One way of increasing the efficiency of such simulation is to partition the landscape so that entities need only traverse its local space for entities that falls within the interaction proximity. This article presents an efficient segmentation algorithm for biotic interactions for research related to the modelling and simulation of biological systems.
