Bio-inspired computation takes inspiration from biological systems in order to perform some form of computation (such as finding a solution to a problem). Examples include evolutionary algorithms; swarm intelligence (for example, ant colony optimisation and particle swarm optimisation); artificial life; and artificial neural networks. Usually for these systems the underlying assumption is that time is linear (i.e., non-branching, where ââ¬Ëbranchingââ¬â¢ time is a term used by concurrent systems meaning that two or more different courses of actions diverge). For example, the possibility of jumping ahead in time, or returning to a past computation, is usually not considered desirable. In addition, the environment and task in which the computational task takes place is usually considered within a single world rather than multiple worlds where computation takes place either in some pre-determined order or in parallel. (Multiple Worlds and Branching Time for Bio-inspired Computation, William J Teahan)
Last date updated on September, 2024
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