I'm wondering if anyone knows of any software techniques taking advantage of biology? For example, in the robotics world, there are tons, but what about software?
Bio-inspired optimization is a term that covers a wide variety of computational approaches that are based on the principles of biological systems. This motivates the application of biology to optimization problems. Biologically inspired computing and optimization is a major subset of natural computation.
Definition. Bioinspired materials are synthetic materials whose structure, properties or function mimic those of natural materials or living matter.
Bio-inspired algorithms, such as genetic algorithms, evolutionary strategy, particle swarm optimization, ant colony optimization, and differential evolution.
Many concepts originally observed in biology have been used in software. For example Genetic Algorithm (GA).
Artificial life (AL) exposes/uses several principles of biology such as resilience to imperfect code snippets, addressing by content, imperfect reproduction (in some implementations, also sexual, i.e. multi-orginanisms-driven, reproduction) and a non-goal-driven utility function. An interesting result of AL, is the spontaneous production of macro phenomenons observed in domains such as ecology or epidemiology (domains largely influenced by biology), such as the emergence of parasites and even that of organisms which take advantage of parasites, or subtle predator-prey relationships.
Maybe software can be said to have gone "full circle" with some experiments in computing which involve real (carbon-based) DNA (or RNA) molecules! The original experiment in this area (PDF link) by Prof. Alderman (of RSA fame), who coded the various elements of a graph-related problem (an hamiltonian graph) with different DNA molecules and let the massive parallel computing power of bio-chemistry do the rest and solve the problem !
Back in the digital world, but with a strong inspiration from biology and indeed from anatomy of the cerebral cortex, and from many theoretical and clinical observations in the neuroscience field, we have Neural Networks (NN). In the area of NN, maybe worthy of a special notice, is Numenta's Hierarchical Temporal Memory model which, although it reproduces the [understanding we have of] the neo-cortex only very loosely, introduces the idea that the very same algorithm is applied in all areas and at all levels of the cognitive process powered by the brains, an idea largely supported by biological, anatomical and other forms of evidence.
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