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?
Biologically inspired software
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If your question means "have biological ideas been used to optimize software?" then Genetic programming (http://en.wikipedia.org/wiki/Genetic_programming) is one example. From the Wikipedia article:
In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. Therefore it is a machine learning technique used to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.
If your question means "what software techniques have been inspired by biology?" then see more generally http://en.wikipedia.org/wiki/Bio-inspired_computing. I would expect that several other methods such as ant-swarms (http://en.wikipedia.org/wiki/Ant_colony_optimization) and Neural Networks (http://en.wikipedia.org/wiki/Neural_network_software) could also be used.
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Artificial Neural Networks are another classic example. The software application tends to be pattern recognition and prediction of behaviour of complex systems.
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Ant colony optimization, a search / optimization method, and Artificial Life like Conway's Game of Life
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Alan Kay (the object technology pioneer) spoke at length about the influence of biology in the OOP paradigm. He's got a series of ideas about how objects are like "cells" and that OOP scales in a similar way to the way that cells can scale to produce massive architectures...
You can follow quite a bit of this in his Turing Award Speech: http://video.google.com/videoplay?docid=-2950949730059754521# -- Skip to about the 30:55 mark
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.